tmp5DB7.tmp

Periodico trimestrale - Sped. in Abb. Post. - D.L. 353/2003 conv. in L. 27/02/2004 n° 46 art. 1, comma 1, DCB PISA Aut. tirb. di Pisa n.5 del 9-3-2000

ISSN 1592-1638

Vol. 16 • N. 3 • September 2014

the official journal of

World Federation for the Treatment of Opiod Dependence

A New Era. Provide Quality Patient Care

For more than 40 years Recki¹ Benckiser is commi¹ed to continuing its long standing support of the addiction medicine community worldwide in order to improve the Quality Patient Care

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Editorial Board Editor Icro Maremmani

Vincent P. Dole Dual Diagnosis Unit, Department of Neurosciences, "Santa Chiara" University Hospital, Pisa, Italy, EU

Associate Editors Thomas Clausen

SERAF, Norwegian Centre for Addiction Research, University of Oslo, Norway

Pier Paolo Pani

Social Health Division, Health District 8 (ASL 8), Cagliari, Italy, EU

Marta Torrens

University of Barcelona, Spain, EU

International Advisory Board Hannu Alho

National Public Health Institute (KTL), University of Helsinki, Finland, EU

Marc Auriacombe

Université Victor Segalen, Bordeaux 2, France, EU

James Bell

South London and Maudsley NHS FoundationTrust & Langston Centre, Sydney, Austrelia

Olof Blix

County Hospital Ryhov, Jönköping, Sweden, EU

Barbara Broers

University Hospital of Geneva, Switzerland

Miguel Casas

University Hospital of "Vall d’Hebron" - University of Barcelona, Spain, EU

Liliana Dell'Osso

Department of Clinical and Experimental Medicine, University of Pisa, Italy, EU

Michael Farrell

National Drug and Alcohol Research Centre, University of New South Wales, Sydney, Australia

Loretta Finnegan

National Institutes of Health, Bethesda, ML, USA, [Retired]

Gabriele Fischer

Addiction Clinic, University of Vienna, Austria, EU

Carla Gambarana

Department of Molecular and Developmental Medicine, University of Siena, Italy Health and Human Development Section, Division for Operations, United Nations Office on Drugs and Crime (UNODC), Vienna University of Cagliari, Italy, EU, [Emeritus]

Gilberto Gerra Gian Luigi Gessa Michael Gossop

Lars Gunne

King’s College, University of London, UK, EU Department of Neuroscience, Institute of Addictive Diseases, University Hospital of Uppsala, Sweden, EU University of Uppsala, Sweden, EU, [Emeritus]

Andrej Kastelic

Center for Treatment of Drug Addiction, University Hospital, Ljubljana, Slovenia, EU

Michael Krausz

St.Paul’s Hospital, University of British Columbia, Canada

Mary Jane Kreek

The Rockfeller University, New York, USA

Evgeny Krupitsky

St. Petersburg Bekhterev Psychoneurological Research Institute, Saint Petersburg, Russia

Mercedes Lovrecic

Institute of Public Health of the Republic of Slovenia, Ljubljana, Slovenia, EU

Joyce Lowinson

Albert Einstein College of Medicine, The Rockfeller University, New York, USA, [Emeritus]

Robert Newman

Baron de Rothschild Chemical Dependency Institute, Beth Israel Medical Center, New York, NY, USA

Charles P. O'Brien

University of Pennsylvania, Phildelphia, USA

Lubomir Okruhlica

Centre for Treatment of Drug Dependencies, Bratislava, Slovak Republic, EU

Mark Parrino

American Association for the Treatment of Opioid Dependence, New York, USA

Einat Peles

Tel-Aviv Sourasky Medical Center, Sackler Faculty of Medicine, Tel Aviv University, Israel

Giulio Perugi

Department of Psychiatry, University of Pisa, Italy, EU

Marc Reisinger

European Opiate Addiction Treatment Association, Brussels, Belgium, EU

Lorenzo Somaini

Addiction Treatment Center, Cossato (Biella), Italy, EU

Marlene Stenbacka

Karolinska Institute, Stockholm, Sweden, EU

Leift Grönbladh

Alessandro Tagliamonte University of Siena, Italy, EU [Retired] Ambros Uchtenhagen Research Foundation on Public Health and Addiction, Zurich University, Switzerland Helge Waal

Center for Addiction Research (SERAF), University of Oslo, Norway, [Emeritus]

George Woody

University of Pennsylvania, Phildelphia, USA

Editorial Coordinators Marilena Guareschi

Association for the Application of Neuroscientific Knowledge to Social Aims, AU-CNS, Pietrasanta, Lucca, Italy, EU "G. De Lisio" Institute of Behavioural Sciences, Pisa, Italy, EU

Matteo Pacini Angelo G.I. Maremmani

Association for the Application of Neuroscientific Knowledge to Social Aims, AU-CNS, Pietrasanta, Lucca, Italy, EU School of Psychiatry, University of Pisa, Italy, EU II level University Master Degree in Addictologia (60 ECTS). School of Psychiatry, University of Pisa, Italy, EU II level University Master Degree in Addictologia (60 ECTS) School of Psychiatry, University of Pisa, Italy, EU II level University Master Degree in Addictologia (60 ECTS)

Luca Rovai Silvia Bacciardi Enrico Massimetti

School of Psychiatry, University of Pisa, Italy, EU

Denise Gazzarrini

School of Psychiatry, University of Pisa, Italy, EU II level University Master Degree in Addictologia (60 ECTS)

Fabio Rugani

II level University Master Degree in Addictologia (60 ECTS)

Publishers Association for the Application of Neuroscientific Knowledge to Social Aims, AU-CNS "From science to public policy"

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Cited in: EMBASE Excerpta Medica Database SCOPUS EMCave Social Sciences Citation Index (SSCI) - Thomson Reuters

Open Access at: http://www.heroinaddictionrelatedclinicalproblems.org

CONTENTS Preventing opioid overdoses: Is the first still the best? Should we go back to the origins?

5

Icro Maremmani and Angelo Giovanni Icro Maremmani

Substance abuse in Romania. A clinical medical-legal perspective

7

Dan Dermengiu, Hostiuc Sorin, Doina Radu, Florina Aciu, Vasile Astarastoae, Beatrice Ioan, Gabriela Constantinescu, Alexandra Enache, Veronica Ciocan, Ioan Talos, Gabriel Gorun, and George Cristian Curca

The role of the opioid system in Eating Disorders. Perspectives for new treatment strategies

15

Luca Rovai, Angelo Giovanni Icro Maremmani, Silvia Bacciardi, Fabio Rugani, Enrico Massimetti, Denise Gazzarrini, Matteo Pacini, Liliana Dell’Osso, and Icro Maremmani

Comparing emotional clarity, emotion experience, and emotion regulation in male heroin addicts with and without withdrawal syndrome

35

Zhao Xin, Xie Lu, Fu Li, Zhou Renlai, Jin Ge,Yang Ling, and Cai Yueyue

Why do heroin users refuse to participate in a heroin-assisted treatment trial?

41

Isabelle Demaret, Géraldine Litran, Cécile Magoga, Clémence Deblire, Anicée Dupont, Jérôme De Roubaix, André Lemaître, and Marc Ansseau

Sexual dysfunction in male patients receiving methadone and buprenorphine maintenance treatment in Iran

49

Shadan Tafreshian, Meisam Javadi, Fariba Fakhraei, and Seyedeh Seddigheh Fatemi

Outcomes of clonazepam maintained benzodiazepine-heroin addicted patients during methadone maintenance: A descriptive case series

55

Angelo Giovanni Icro Maremmani, Silvia Bacciardi, Fabio Rugani, Luca Rovai, Enrico Massimetti, Denise Gazzarrini, Liliana Dell’Osso, Pier Paolo Pani, Matteo Pacini, and Icro Maremmani

Gender differences in severity of addiction in opiate-dependent outpatients

65

Marcela Mezzatesta-Gava, Carlos Roncero, Laia Rodriguez-Cintas, Gideoni Fuste, Carmen Barral, Nieves Martinez-Luna, Miquel Casas, and Laia Miquel

Limbic system irritability and drug dreams in heroin-addicted patients

75

Claudio Colace, Sergio Belsanti, and Antonia Antermite

Induction and switch to buprenorphine-naloxone in opioid dependence treatment: Predictive value of the first four weeks

87

Sabine M. Apelt, Norbert Scherbaum, and Michael Soyka

Using oral or i/m morphine for rapid tolerance assessment in patients starting methadone maintenance: A proposal for discussion based on over 25 years of experience

99

Colin Brewer

30 years of Naloxone Massimo Barra and Vittorio Lelli

101

Editorial Heroin Addict Relat Clin Probl 2014; 16(3): 5-6

Preventing opioid overdoses: Is the first still the best? Should we go back to the origins? Icro Maremmani1,2,3 and Angelo Giovanni Icro Maremmani1,2 1. Vincent P. Dole Dual Diagnosis Unit, Department of Neurosciences, Santa Chiara University Hospital, University of Pisa, Italy, EU 2. Association for the Application of Neuroscientific Knowledge to Social Aims (AU-CNS), Pietrasanta, Lucca, Italy, EU 3. G. De Lisio Institute of Behavioural Sciences, Pisa, Italy, EU

Philip Seymour Hoffman's death, in February, shocked the population as well as all professionals involved in the addiction field. He was the latest of a sequence of celebrities (including Anna Nicole Smith, Chris Kelly, Michael Jackson and Whitney Houston) who have died from drug-related problems. These are the very moments at which the media shed light on opioid addiction by looking at its more dramatic events – deaths from an overdose. Suddenly, the media can reflect on the ‘democracy’ of opioid addiction, which can disrupt the lives of anyone, from the homeless to movie stars, making them all equal on medical grounds. This shocking news is in open contrast with the capability of agonist opioid treatment to treat opioid addiction, as first described by Vincent P. Dole almost 50 years ago [2], and to limit overdose mortality [1, 4]. Agonist opioid treatment is a life-saving treatment, and the best made available by addiction medicine, to deal with the severe chronic mental illness that opioid addiction is. When applied using the correct methodology [7], agonist opioid treatment has proven to be highly effective and over the last few decades it has significantly reduced deaths related to substance use [10]. Despite the evidence-based data, despite the high percentages of those surviving in treatment, agonist opioid treatment has always been hampered,

whereas other models of treatment, such as detoxification, drug-free rehabilitation and psychotherapy, have been encouraged. At the present time, in 2014, agonist opioid treatment is still not provided in Russia [9], whereas advances are occurring in South Asia. Even where agonist opioid treatment is performed, an incorrect application of treatment methodology can often be observed [8]. There is the need to strictly implement the 4 phases of treatment (induction phase, stabilization phase, maintenance phase, medically supervised withdrawal phase), and to reach blocking dosages instead of anti-withdrawal ones, together with rehabilitation through behavioural and social adjustment. The proper methodology is what makes it possible to achieve the same results that Dole had in treating his criminal addicts [3], while also having a positive impact on psychopathology and polyabuse levels [5, 6]. A comprehensive treatment includes various different levels. Harm reduction is one of them, but it is a model that is not directly linked with the preeminent criterion of a correct application of agonist opioid treatment methodology, which means there is absolutely no need to create a situation of conflict by setting harm reduction against agonist opioid treatment. We think that it is now time to refer back to the teachings of Dole – and his basic concept of correctly applying the methodology of agonist opioid

Corresponding author: Angelo Giovanni Icro Maremmani, MD; Association for the Application of Neuroscientific Knowledge to Social Aims (AU-CNS), Via 20 settembre 83, Pietrasanta, Lucca, Italy, EU. Phone: +390584 790073; e-mail: [email protected]

5

Heroin Addiction and Related Clinical Problems 16(3): 5-6

treatment, which is what makes it possible to successfully treat opioid addiction. Politicians and the media can both play a crucial role in positively influencing the general population to appreciate the advantages of agonist opioid treatment, while politicians can facilitate access to the treatment (e.g. by eliminating the problem of long waiting lists). In referring now specifically to the medical field, there is an ongoing need to educate doctors in Medical Schools and Universities about the effectiveness of a correct agonist opioid treatment, and we can confidently saying that the best harm reduction takes the form of a comprehensive agonist opioid treatment. After 50 years, we are ready to re-launch Dole’s teachings by acting as a ‘neo-Dolian’ group, and defining the best treatment solution as having been the first one.

6. Maremmani A. G. I., Rovai L., Rugani F., Bacciardi S., Dell’Osso L., Maremmani I. (2014): Substance abuse and psychosis: the strange case of opioids. Eur Rev Med Pharmacol Sci. 18: 287-302. 7. Maremmani I. (2009): The Principles and Practice of Methadone Treatment. Pacini Editore Medicina & AUCNS, Pisa. 8. Maremmani I., Maremmani A. G. I., Lubrano S., Nardini R., Dell’Osso L., Pacini M. (2013-Ahead of Print): Who are resistant patients? Quality of treatment and disease control. Addict Disord Their Treatment. 9. Maremmani I., Pacini M., Pani P. P., Parrino M. (2006): Say “Yes” to Methadone and Buprenorphine in Russian Federation. Heroin Addict Relat Clin Probl. 8(2): 5-22. 10. Mattick R. P., Breen C., Kimber J., Davoli M. (2003): Methadone maintenance therapy versus no opioid replacement therapy for opioid dependence. Cochrane Database Syst Rev(2): CD002209.

References 1. Caplehorn J. R., Drummer O. H. (1999): Mortality associated with New South Wales methadone programs in 1994: lives lost and saved. Med J Aust. 170(3): 104109. 2. Dole V. P., Nyswander M. E. (1965): A medical treatment for diacetylmorphine (heroin) addiction: A clinical trial with methadone hydrocloride. JAMA. 193: 80-84. 3. Dole V. P., Nyswander M. E., Warner A. (1968): Successful treatment of 750 criminal addicts. JAMA. 206: 2708-2711. 4. Gronbladh L., Ohlund L. S., Gunne L. M. (1990): Mortality in heroin addiction: impact of methadone treatment. Acta Psychiatr Scand. 82(3): 223-227. 5. Maremmani A. G. I., Rovai L., Pani P. P., Pacini M., Lamanna F., Rugani F., Schiavi E., Dell’Osso L., Maremmani I. (2011): Do methadone and buprenorphine have the same impact on psychopathological symptoms of heroin addicts? Ann Gen Psychiatry. 10:17.

Role of the funding source No sponsor played a role in this editorial. Contributors Authors revised and approved the final form of the editorial. Conflict of interest Authors declared no conflict of interest. IM served as Board Member for Reckitt Benckiser Pharmaceuticals, Mundipharma, D&A Pharma, and Lundbeck.

Received and Accepted August 22, 2014 -6-

Regular article Heroin Addict Relat Clin Probl 2014; 16(3): 7-14

Substance abuse in Romania. A clinical medical-legal perspective Dan Dermengiu 1, Hostiuc Sorin 1, Doina Radu 2, Florina Aciu 2, Vasile Astarastoae 3, Beatrice Ioan 3, Gabriela Constantinescu 4, Alexandra Enache 5, Veronica Ciocan 5, Ioan Talos 6, Gabriel Gorun 7, and George Cristian Curca 1 1 Carol Davila University of Medicine and Pharmacy, Dept. of Legal Medicine and Bioethics, National Institute of Legal Medicine, Dept. of Forensic Pathology, Bucharest, Romania, EU 2 National Institute of Legal Medicine, Dept. of Forensic Toxicology, Bucharest, Romania, EU 3 Iasi Institute of Legal Medicine, Dept. of Forensic Pathology, Iasi, Romania, EU 4 Iasi Institute of Legal Medicine, Dept. of Forensic Toxicology, Iasi, Romania, EU 5 Timisoara Institute of Legal Medicine, Dept. of Forensic Pathology, Timisoara, Romania, EU 6 Timisoara Institute of Legal Medicine, Dept. of Forensic Toxicology, Timisoara, Romania, EU 7 National Institute of Legal Medicine, Dept. of Forensic Pathology, Bucharest, Romania, EU

Summary Objective. In Romania medical-legal studies on the pattern of drug consumption have not yet been conducted nationwide; the purpose of this study was, therefore, to determine whether such a pattern could be identified. Methods. A total number of 577 analyses were performed during a three-year period on people suspected of non-lethal substance abuse, in more than two-thirds of the counties in Romania. Preliminary tests were conducted using immunoassay tests (blood or urine) and confirmatory tests were carried out using either GC-MS or HPLC. Results. 240 cases (41.6%) were negative while 327 cases (58.4%) tested positive for illegal drugs, central nervous system medication or both. Men represented 89.5% of all cases, while women accounted for only 10.5%. The pattern of substance abuse varied significantly, depending on the geographical area. In most cases, the identified drugs of abuse were cannabinoids and opiates, with a significantly different distribution of cases, depending on the geographical area. The highest number of positive cases was identified in the month of October, whereas the smallest numbers were identified in July and December. The annual trend of consumption revealed a significant decrease in the analysed substances in 2011. Conclusions. Our study has determined the presence of a specific pattern of consumption in different geographical areas – a result that suggests the need for more targeted prevention programmes, addressing local particularities in consumption behaviours. A significant decrease in the identification of drugs of abuse in the third year of our study, combined with data attesting the significant increase in the consumption of legal highs suggests that the forensic toxicology laboratories need to be equipped with apparatus able to detect these newer substances of abuse more efficiently. Key Words: non-lethal substance abuse in Romania; drug abuse pattern in Romania; opiates; legal highs

1.

Introduction

Substance abuse and misuse is a severe problem worldwide, affecting more than 185 million people [17]. It leads annually to more than 200,000 deaths due to illicit drugs only [34], causes a significant increase in violence-related traumas including suicides [14, 16, 24, 31], domestic violence [10, 15, 21, 27, 29, 39], interpersonal violence by firearms and sharp force injuries [34], an increased risk of contracting various viral and bacterial infections [3, 6, 7, 9, 11,

22, 25], and so on. The pattern of consumption is highly variable between countries [4, 5, 8, 12, 13, 19, 20, 28, 30, 33, 38], and in the same country between different social or economic groups. These variations are of the uttermost importance for physicians (who may not have the time to perform a proper toxicological analysis in the emergency room, and must initially act on incomplete data), forensic toxicologists and pathologists (who can use more targeted procedures, initially directed towards the most frequently used drugs), or police officers (who have to screen driv-

Corresponding author: Sorin Hostiuc, Carol Davila University of Medicine and Pharmacy, Dept of Legal Medicine and Bioethics, National Institute of Legal Medicine, Dept of Forensic Pathology, Bucharest, Romania, Vitan Barzesti 9, 042122, Bucharest, Romania, EU; E-mail: [email protected];

7


ers using rapid tests, and need to know what kind of screening tests to use in traffic). In Romania, nationwide studies on the pattern of consumption were only conducted using sociological surveys [1, 2]; toxicological studies were only carried out in specific counties [13, 23, 28, 32, 35] and/or specific groups [26, 32, 35]. The purpose of this article was to determine the pattern of substance abuse in Romania by using data obtained from medical-legal services. 2.

Methods

The study was carried out in three medical-legal institutions (in Bucharest, Iasi, and Timisoara) that perform forensic toxicology tests for more than twothirds of the Romanian counties. Preliminary screen-

ing was performed using immunoassay tests (blood or urine), and confirmatory tests were conducted using GC-MS for illegal substances, or HPLC for Central Nervous System (CNS) medication, including barbiturates, benzodiazepines and anti-psychotics. Each institute used its own detection methods. A total number of 577 analyses were performed between October 2008 and September 2011, of which 79.55% (459 cases) were done at the request of the police, 12.82% (75 tests) were done in response to a personal request and 7.63% (44 tests) were done at the request of various other institutions. Age could only be obtained in 193 cases, as the bulletins associated with the sampling biological products differed between counties, and some did not include age as a mandatory field. The results were then gathered using

Table 1. Distribution of positive cases between sex and age groups Substance

Positives (rePositives Positives by other (requested by Pearson χ2 for (requested by quested official institu- the person in requests) the police) tions) question)

Morphine

45

10

3

13.428 (p=0.001)

Methadone

19

4

0

Tramadol Pethidine

3 0

1 2

0 0

Cocaine

8

0

0

Cannabinoids

221

3

3

Amphetamines

2

0

1

JWP_018

7

0

0

MDMA

3

0

0

Ketamine

5

0

0

MDPPP/MPP

0

0

1

5.675 (p=0.059) n.a. n.a. 1.011 (p=0.603) 49.609 (p=0.000) n.a. 0.882 (p=0.644) n.a 0.626 (p=0.731) n.a

Benzodiazepines

27

7

4

14.384 (p=0.001)

Zopiclone Antidepressants

2 2

0 2

0 1

Antiepileptic

4

1

1

Antipsychotic

3

1

0

n.a n.a. 3.353 (p=0.187) n.a.

Barbiturates

7

3

3

18.091 (p=0.000)

-8-

Comments Tests for morphine were significantly more frequently positive when the analysis was requested by other official institutions

Tests for benzodiazepines were significantly less frequently positive when the police requested the analyses.

Tests for barbiturates were significantly less frequently positive when the police requested the analyses.

D. Dermengiu et al.: Substance abuse in Romania. A clinical medical-legal perspective

a common reporting methodology based on standardized forms and inserted into an SPSS database. Statistical analysis was done with SPSS v.20 for Mac OS software. The following statistical tests were used: descriptive statistics (frequencies, mean, standard deviation, range, minimum, maximum), and cross-tabulations (using the χ2 Pearson test to test the presence of a significant correlation between descriptive data). A p value below 0.05 was considered significant. 3.

Results

Of the 577 analyses that were performed, 240 (41.6%) tested negative both for illegal substances and CNS-medication, 308 (53.38%) tested positive for drugs of abuse, six for CNS-medication (1.04%) and 23 (3.98%) both for drugs of abuse and CNS-

medication. In 288 cases a single substance was identified (85.46%), in 31 cases two substances were identified (9.20%), and in 18 (5.34%) there were more than two. Men accounted for 89.5% of all cases, and had a mean age of 25.52 years (ranging between 16 and 50) while women only represented 10.5% of all cases, had a higher mean age (29.84, and a range between 15 and 73). Age distribution of people testing positive was as follows: below 20 years – 54 positive cases (27.98%), 20-25 years – 67 positive cases (34.71%), 26-30 years – 38 positive cases, (19.69%), 31-40 years – 26 positive cases (13.47%) and over 40 years – 8 cases (4.15%). Of the 459 tests requested by the police, 159 (34.65%) were negative, and 300 (65.35%) were positive. Of the 44 tests requested by other institutions, 22 were negative (50%) and 22 were positive (50%). Of the 74 tests done in response

Table 2. Distribution of cases on the basis of the person/agency who asked for the procedure Substance

Positives (rePositives Positives quested by other (requested Pearson χ2 for (requested by official institu- the person by in requests) the police) tions) question)

Morphine

45

10

3

13.428 (p=0.001)

Methadone

19

4

0

Tramadol Pethidine

3 0

1 2

0 0

Cocaine

8

0

0

Cannabinoids

221

3

3

Amphetamines

2

0

1

JWP_018

7

0

0

MDMA

3

0

0

Ketamine

5

0

0

MDPPP/MPP

0

0

1

5.675 (p=0.059) n.a. n.a. 1.011 (p=0.603) 49.609 (p=0.000) n.a. 0.882 (p=0.644) n.a 0.626 (p=0.731) n.a

Benzodiazepines

27

7

4

14.384 (p=0.001)

Zopiclone Antidepressants

2 2

0 2

0 1

Antiepileptic

4

1

1

Antipsychotic

3

1

0

n.a n.a. 3.353 (p=0.187) n.a.

3

18.091 (p=0.000)

Barbiturates

7

3

Comments Tests for morphine were significantly more frequently positive when the analysis was requested by other official institutions

Tests for benzodiazepines were significantly less frequently positive when the police requested the analyses.

Tests for barbiturates were significantly less frequently positive when the police requested the analyses.

-9-


250

227

200

150

100 58 50

38

23

13

8

7

6

5

5

19

0

Figure 1. Relative frequencies of the substances identified

to a personal request, 59 were negative (79.72%) and 15 (20.28%) were positive. In 14 cases a positive drug test was associated with a positive blood-alcohol test. The substances most frequently identified in our tests were: cannabinoids, with 227 positive results, followed by morphine with 58 cases, benzodiazepines with 38, methadone with 23, and barbiturates with 13 cases (see Tables 1 and 2 and Figure 1). The distribution of positive cases between the three centres of analysis was as follows: 122 positive cases (36.2%) were identified in the Bucharest Institute (which is the centre assigned to counties in the Southern part of Romania), 119 cases (35.3%) were identified in the Iasi Institute (the centre assigned to counties in the North-Eastern part of Romania), and 96 cases (28.48%) were identified in the Timisoara Institute (the centre assigned to the counties in the Western part of Romania). The relative frequencies of the drugs of abuse differed sharply between the three centres. In the Bucharest Institute opiates were the most frequently identified substances with 62 cases (50.81%, of which 37 tested positive for morphine, 20 for methadone, three for Tramadol, and two for Pethidine), followed by cannabinoids in 45 cases (36.88%), and benzodi- 10 -

azepines in 31 (25.4%). In 31 cases more than one active substance was identified. At the Iasi institute cannabinoids were identified in 102 cases (85.71%), followed by JWP_18 in seven cases (5.88%), benzodiazepines in six (5.04%), and opiates in five (4.20%). In the Timisoara Institute the most frequently identified substances were cannabinoids (80 cases, 83.33%), followed by opiates (20 cases, 20.83%) and cocaine (six cases, 6.25%). The differences were statistically significant. The most positive samplings occurred in October (61 cases, 18.5%), whereas the lowest numbers of positive cases occurred in July (16 cases, 4.74%) and December (11 cases, 3.27%) (see Figure 2). In year 1 (October 2008 - September 2009) 131 positive cases (38.87%) were identified, in year 2 (October 2009 September 2010) 125 cases (37.09%) were identified, and in year 3 (October 2010 - September 2011) 81 cases (24.04%) were identified. 4.

Discussion

Between 2008 and 2010 we identified a rise in the number of positive cases, followed by a fall in 2011. Even if the data from 2011 were only based on the first ten months, the value obtained is about


half the value calculated for 2010. The main reason is a dramatic increase in the consumption of so-called “legal drugs” [18, 19, 28, 36, 37], which often need more specialized equipment like liquid chromatography – mass spectrometry – mass spectrometry (LCMS-MS) for a positive identification. This shift in consumption is suggested by a study carried out in 2009 and the first six months of 2010 on the distribution of non-fatal emergencies associated with drug consumption [2]. In 2009, 999 non-lethal drug-related emergencies were identified in Romania; of these 258 were opiate-related and 86 were cases of acute intoxication induced at the legal highs (as declared by the patients). In the first six months of 2010, 934 non-lethal drug related emergencies were identified, of which legal highs accounted for 236 and opiates for 126 cases. Cannabinoid-related emergencies almost doubled (48 cases in 2009, 49 cases in the first six months of 2010). The pattern of consumption is similar to the one suggested by a study based on a survey involving Romanian high school students[2], in which cannabinoids were the most frequently used type of drug (34.1% of the students declaring substance abuse said they had used marijuana, 8.6% cannabis, 6.5% hash-

ish, 3.6% weeds followed by drugs inducing “legal highs” like Magic (3.6%), Spice (2.2%), and Ecstasy (3.6%). Heroin was only used by 1.4% of high school students [2]. We have found significant differences between the profiles of drug consumption in different regions; in the capital and the counties surrounding it, the most frequently used drugs were opiates, but in other regions cannabinoids were far more frequently identified. An accurate knowledge of the patterns of consumption prevalent in different geographical areas may help policymakers to develop specific, targeted prevention programmes. By analysing the number of cases per month we have found that the lowest numbers of positive cases have been found in July and December (months in which a large number of people are on vacation), while the highest numbers were recorded in October (the month in which all students go back to their schools/universities). The most likely explanation is that consumption is associated with (1) mobility – its prevalence is higher in people who travel (whereas it falls in the months when they stay in their places of residence) or (2) study (it rises when they go back to school after holidays) in locations different from

70

18.15%

61

60 50

11.60%

40 30 20

9.82%

8.93% 7.14%

24

33

30

5.65%

19

39 8.63%

8.63%

29

29

6.25%

21

10

7.14%

24 4.76%

16

3.27%

11

0

Figure 2. Distribution of cases on a monthly basis

- 11 -


those where they live. 5.

Conclusions

Our study has determined the presence of a specific pattern of consumption in each of a number of different geographical areas, a result which suggests the need for more targeted prevention programmes, so allowing particularities in consumption behaviours to be investigated. The significant fall recorded in the identification of drugs of abuse in the third year of our study, combined with data documenting the significant rise in intoxication induced at the legal highs, suggests that the forensic toxicology laboratories we have studied need to be equipped with LC-MS-MSs. References 1. International Strategic Report regarding narcotics control. DEA Report for 2008., 2009, Feb 27, Romanian National Antidrug Agency (Agentia Nationala Antidrog). 2. National Report on Drug Situation 2010. ROMANIA. New Developments, Trends and In-depth Information on Selected Issues, 2011, National Anti-Drug Agency. 3. Abraham A. J., O’brien L. A., Bride B. E., Roman P. M. (2011): HIV/AIDS services in private substance abuse treatment programs. Drug Alcohol Depend. 115(1-2): 16-22. 4. Acker C. J. (2010): How crack found a niche in the American ghetto: The historical epidemiology of drug-related harm. Biosocieties. 5(1): 70-88. 5. Aguilar-Gaxiola S., Medina-Mora M. E., Magana C. G., Vega W. A., Alejo-Garcia C., Quintanar T. R., Vazquez L., Ballesteros P. D., Ibarra J., Rosales H. (2006): Illicit drug use research in Latin America: Epidemiology, service use, and HIV. Drug Alcohol Depend. 84: S85-S93. 6. Bal B., Mitra R., Mallick A. H., Chakraborti S., Sarkar K. (2010): Nontobacco substance use, sexual abuse, HIV, and sexually transmitted infection among street children in Kolkata, India. Subst Use Misuse. 45(10): 1668-1682. 7. Bauer L. O. (2011): Interactive effects of HIV/AIDS, body mass, and substance abuse on the frontal brain: a P300 study. Psychiatry Res. 185(1-2): 232-237. 8. Brvar M., Mozina M. (2008): DRUG POISONING IN SLOVENIA. Zdravniski Vestnik-Slovenian Medical Journal. 77(1): 39-45. 9. Chan Y. F., Passetti L. L., Garner B. R., Lloyd J. J., Dennis M. L. (2011): HIV risk behaviors: risky sexual activities and needle use among adolescents in substance abuse treatment. AIDS Behav. 15(1): 114-124. 10. Curca G. C., Buda O., Capatana C., Marinescu M., Hostiuc S., Dermengiu D., Cartina C., Cretoiu V. A., Stoica N. - 12 -

A., Badescu I., Voinea M., Darie C., Apostu I., Banciu D. P. G., Balica E. G., Brezeanu O., Constantinescu A., Gheorghiu V., Balan L. (2008): Study on domestic violence: a legal medicine perspective. Romanian Journal of Legal Medicine. 16(3): 226-242. 11. Delorenze G. N., Weisner C., Tsai A. L., Satre D. D., Quesenberry C. P., Jr. (2011): Excess mortality among HIV-infected patients diagnosed with substance use dependence or abuse receiving care in a fully integrated medical care program. Alcohol Clin Exp Res. 35(2): 203-210. 12. Delva J., Van Etten M. L., Gonzalez G. B., Cedeno M. A., Penna M., Caris L. H., Anthony J. C. (1999): First opportunities to try drugs and the transition to first drug use: Evidence from a national school survey in Panama. Subst Use Misuse. 34(10): 1451-1467. 13. Dermengiu D., Radu D., Aciu F., Broscauceanu A., Sereteanu L., Gorun G., Curca G. C., Hostiuc S. (2011): Drugs of abuse identified in the National Institute of Legal Medicine Mina Minovici Bucharest 2010. Romanian Journal of Legal Medicine. 19(3): 229-232. 14. Dhossche D. M., Meloukheia A. M., Chakravorty S. (2000): The association of suicide attempts and comorbid depression and substance abuse in psychiatric consultation patients. Gen Hosp Psychiatry. 22(4): 281-288. 15. Easton C. J., Lee B., Wupperman P., Zonana H. (2008): Substance abuse and domestic violence interventions: the need for theoretical based research. Am J Addict. 17(4): 341-342. 16. Epelbaum C., Taylor E. R., Dekleva K. (2010): Immigration trauma, substance abuse, and suicide. Harv Rev Psychiatry. 18(5): 304-313. 17. Factsheets, W. (2012). "Management of substance abuse. The global burden." Retrieved 12/01, 2012, from http://www.who.int/substance_abuse/facts/ global_burden/en/index.html. 18. Gorun G., Curca G. C., Hostiuc S., Buda O. (2011): “Legal highs” in Romania: historical and present facts. Romanian Journal of Legal Medicine. 19(1): 73-76. 19. Gorun G., Dermengiu D., Curca G. C., Hostiuc S., Ioan B., Luta V. (2010): Toxicological drivers issues in “legal highs” use. Romanian Journal of Legal Medicine. 18(4): 271-278. 20. Hill S. L., Thomas S. H. L. (2011): Clinical toxicology of newer recreational drugs. Clinical Toxicology. 49(8): 705-719. 21. Hostiuc S., Curca C. G., Dermengiu D. (2011): CONSENT AND CONFIDENTIALITY IN MEDICAL ASSISTANCE FOR WOMEN VICTIMS OF DOMESTIC VIOLENCE. Revista Romana De Bioetica. 9(1): 96-107. 22. Hostiuc S., Curca G. C., Ceausu M., Rusu M. C., Niculescu E., Dermengiu D. (2011): Infectious risks in autopsy practice. Romanian Journal of Legal Medicine. 19(3): 183-188. 23. Jung H., Matei D., Hecser L., Bohnert M., Pollak S.


(2007): Pulmonary pathology in drug related deaths. Romanian Journal of Legal Medicine. 15(2): 83-90. 24. Karch D. L., Barker L., Strine T. W. (2006): Race/ ethnicity, substance abuse, and mental illness among suicide victims in 13 US states: 2004 data from the National Violent Death Reporting System. Inj Prev. 12 Suppl 2: ii22-ii27. 25. Lucas G. M. (2011): Substance abuse, adherence with antiretroviral therapy, and clinical outcomes among HIV-infected individuals. Life Sci. 88(21-22): 948-952. 26. Macovei R. A., Danescu I. L., Ionica M., Caragea G., Cioca G. (2008): Acute poisoning cases admitted in the ICUII Toxicology-Emergency Clinical Hospital Bucharest in 10 years (1998-2007). Toxicology Letters. 180: S129-S130. 27. Martin S. L., Moracco K. E., Chang J. C., Council C. L., Dulli L. S. (2008): Substance abuse issues among women in domestic violence programs: findings from North Carolina. Violence Against Women. 14(9): 985-997. 28. Morar S., Peteanu I., Nicolau C., Olariu N. (2011): Typical and atypical psyhotropic substances detected during July 2009-March 2011 in the Forensic Department of Sibiu County. Romanian Journal of Legal Medicine. 19(2): 151-156. 29. Najavits L. M., Sonn J., Walsh M., Weiss R. D. (2004): Domestic violence in women with PTSD and substance abuse. Addict Behav. 29(4): 707-715. 30. Narenjiha H., Rafiey H., Jahani M. R., Assari S., Moharamzad Y., Roshanpazooh M. (2009): Substance-Dependent Professional Drivers in Iran: A Descriptive Study. Traffic Injury Prevention. 10(3): 227-230. 31. Rowan A. B. (2001): Adolescent substance abuse and suicide. Depress Anxiety. 14(3): 186-191. 32. Sorodoc V., Jaba I. M., Lionte C., Mungiu O. C., Sorodoc L. (2011): Epidemiology of acute drug poisoning in a tertiary center from Iasi County, Romania. Hum Exp Toxicol. 30(12): 1896-1903. 33. Steentoft A., Simonsen K. W., Linnet K. (2010): The Frequency of Drugs Among Danish Drivers Before and After the Introduction of Fixed Concentration Limits. Traffic Injury Prevention. 11(4): 329-333. 34. Toprak S., Sam B., Akgul E., Silan C., Baysal E. (2010): Psychoactive Drug Related Traumatic Deaths in

Istanbul between 1990-2000. Romanian Journal of Legal Medicine. 18(1): 69-74. 35. Vernic C., Ursoniu S., Vlaicu B., Apostol S. (2010): Prevalence and perceived risks of drug use among undergraduate students from Timis county: a crosssectional study. AnaleSeria Informatica. VIII (2). 36. Vlase L., Popa D.-S., Loghin F., Leucuta S. E. (2009): High-throughput toxicological analysis of Methamphetamine, MDA and MDMA from human plasma by LC-MS/MS. Romanian Journal of Legal Medicine. 17(3): 213-220. 37. Vlase L., Popa D.-S., Zaharia D., Loghin F. (2010): High-throughput toxicological analysis of Delta 9-THC and 11-nor-9-carboxy-Delta 9-THC by LC/ MS/MS. Romanian Journal of Legal Medicine. 18(2): 133-140. 38. Vrublevska K., Rukmane J., Burmistrs R., Sipols J., Muceniece R. (2008): Dispensing of psychotropic drugs to adults in community pharmacies in Latvia. Pharmacy World & Science. 30(6): 934-939. 39. Zilberman M. L., Blume S. B. (2005): [Domestic violence, alcohol and substance abuse]. Rev Bras Psiquiatr. 27 Suppl 2: S51-55.

Acknowledgement This article was supported by a UEFISCDI Grant, Programme entitled “Parteneriate in Domenii Prioritare”, No. 42153/2008. Role of the funding source Public finances (National Research Programme). Contributors All authors were involved in the study design, had full access to the survey data and analyses, and interpreted the data, critically reviewed the manuscript and had full editorial control, including final responsibility for the decision to submit the paper for publication. Conflict of interest None

Received August 14, 2013 - Accepted January 26, 2014 - 13 -


The role of the opioid system in Eating Disorders. Perspectives for new treatment strategies Luca Rovai 1, Angelo Giovanni Icro Maremmani 1,2, Silvia Bacciardi 1, Fabio Rugani 1, Enrico Massimetti 1, Denise Gazzarrini 1, Matteo Pacini 3, Liliana Dell’Osso 4, and Icro Maremmani 1,2,3 1 Vincent P. Dole Dual Diagnosis Unit, Department of Neurosciences, Santa Chiara University Hospital, University of Pisa, Italy, EU 2 Association for the Application of Neuroscientific Knowledge to Social Aims (AU-CNS), Pietrasanta, Lucca, Italy, EU 3 G. De Lisio Institute of Behavioral Sciences, Pisa, Italy, EU 4 Department of Clinical and Experimental Medicine, Section of Psychiatry, University of Pisa, Italy, EU

Summary Introduction: Growing evidence drawn both from observational and biological sources supports the hypothesis that eating disorders share the feature of inducing an alteration in the reward system, with a central role being played by opioid neuropeptides. Aims: To estimate i) epidemiological and clinical correlations between opioid use disorder and eating disorders; ii) the nature of the correlation between opioid medications, feeding behaviours and eating disorder symptoms; iii) the feasibility of using opioid medications in the management of eating disorders, especially anorexia nervosa, bulimia nervosa and binge eating disorder; iiii) the risk-benefit ratio of opioid medications compared with that of medications traditionally used to treat eating disorders. Methods: Overview after a thorough search on the “Scopus data base”. Results: We found few available data on the correlations between opiate addiction and eating disorders, whether on the epidemiological or the clinical plane. Opioid full and partial agonists seem to present a promising profile of effects that could be useful in treating anorexia nervosa. Opioid antagonists have been shown to be effective on both bulimia nervosa and binge eating disorders. Nalmefene should be preferred to naltrexone in bulimic patients of normal weight who are able to benefit from a double stabilization. Conclusions: Despite the scarcity of clinical and epidemiological data on the correlations between eating disorders and opiate addiction, evidence from both human and animal studies prompts the suggestion that opioid medications can play a far from negligible role in the treatment of eating disorders. Key Words: reward system, opioid agents, eating disorders, feeding behaviours, treatment strategies

1.

Background

1.1. Neurobiology of reward system The reward system is a relatively well-known form of brain circuitry that plays a central role in instinctual drives, such as those involved in sexual, aggressive and feeding behaviours. It includes the dopamine-containing neurons of the ventral tegmental area, nucleus accumbens, and prefrontal cortex, and has the task of reinforcing behaviours that share the property of being pleasurable and rewarding [21, 119, 124, 160, 161]. Closely related to one another, reward and reinforcement are terms that offer an objective way of de-

scribing the positive value that an individual ascribes to an object, behavioural act or internal physical state. Primary rewards include those that are required for the survival of the species; secondary rewards derive their value from primary rewards, and can be produced experimentally by pairing a neutral stimulus with a known reward. Money is a good example [83, 159]. Diametrically opposed to reward is punishment, which characterizes painful and unpleasant experiences. Individuals actively avoid punishing experiences. Just as ‘reward’ and ‘reinforcement’ describe the effects of positive experiences, ‘punishment’ and ‘avoidance’ offer an objective way of describing the negative value that an individual ascribes to an object,

Corresponding author: Icro Maremmani, MD; Vincent P. Dole Dual Diagnosis Unit, Department of Neurosciences, Santa Chiara University Hospital,University of Pisa, Via Roma, 67 56100 PISA, Italy, EU. Phone +39 0584 790073 Fax +39 0584 72081; E-Mail: [email protected]

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behavioural act or internal physical state. Rewards are generally considered more effective than punishment in modifying human behaviour [36, 38]. The reward system has been widely studied in the field of substance use disorders, which gives us an idea of the neurotransmitters involved. All addictive drugs increase dopamine release in the mesolimbic pathway [38], but it needs to be borne in mind that dopamine is not the only neurotransmitter involved in the acute reinforcing effects of abused drugs. Other neurotransmitters include opioid peptides, which mediate the reinforcing effects of opiates, γ-aminobutyric acid (GABA), which mediates the reinforcing effects of alcohol and benzodiazepines, glutamate, neuropeptide Y, and the glucocorticoids belonging to the hypothalamic-pituitary-adrenal axis [6, 31, 85, 86, 143]. When the reward system is repeatedly stimulated by a pleasurable experience, it can develop neuroadaptive changes that, thanks to the participation of memory functions, ultimately lead to learning phenomena [136]. While being adaptive in most of the activities of daily life, learning can become maladaptive in many behavioural domains, which correspond to substance abuse behavioural dependences and eating disorders [67, 120]. 1.2. The role of opioids in reward activity From a hierarchical point of view the opioid system has a dominant position within the reward system. It consists of three G protein-coupled receptors (μ, δ, and κ), which are stimulated by a family of endogenous peptides (enkephalins, dynorphins and endorphins), and are responsible for the control of pain, reward, attachment and addictive behaviours. The opioid receptors are mainly found in the central and peripheral nervous system and in the gastrointestinal tract; they share a variety of properties, but some distinctive traits can be highlighted [3, 51, 68, 93, 140]. Mu receptors, stimulated by endorphins, are the principal opioid receptors, as they are responsible for most of the therapeutic and addictive properties of opioids. Their activation promotes the release of dopamine in the reward pathway, inducing a state of euphoria. Other effects mediated by μ receptors include respiratory depression, suppression of the cough reflection, nausea, vomiting and myosis, the reduction of intestinal secretion and motility, and an increase in the time transit of intestinal material [28, 45, 90, 93, 140, 150]. - 16 -

Delta receptors have enkephalins as their endogenous ligands. Their activation produces some analgesia and respiratory depression, even if less than that of μ-opioid agonists, and also, to some extent, an antidepressant activity [7, 40, 84, 90, 140, 163]. Kappa receptors bind the opioid peptide dynorphin as their primary endogenous ligand. Their activation is thought to mediate the perception of pain, consciousness, mood stability and motor control [90, 93, 140, 163]. 1.3. The role of reward in eating disorders Eating disorders are a heterogeneous group of diseases distinguished by a persistent disturbance of an eating-related behaviour that significantly impairs physical health or psychosocial functioning [1]. Over the past few decades the boundaries of this class of disorders have been expanding, with the inclusion in the common diagnostic system of new nosographic entities, other than anorexia and bulimia nervosa. Parallel individual disorders have been differentiated both on the epidemiological and the clinical plane. With regard to anorexia and bulimia nervosa, they have their initial onset between 10 and 20 years of age, and carry the burden of a high risk of mortality. The overall incidence of anorexia nervosa has remained stable over the last few decades, but there has been an increase in the high-risk group of 15-19 year old girls. More specifically, the incidence of bulimia may have fallen since the early nineties of the last century. It is well known that anorexia nervosa carries the highest risk of mortality in the entire class of diseases. Although bulimia responds better to treatment, it too brings with it a considerable risk of mortality, and is closely related to suicide [8, 24, 34, 113, 125]. The pathophysiology of eating disorders is far from having been adequately elucidated, and various classes of neurotransmitter systems have been discussed in attempting to explain the behavioural alterations of patients suffering from this class of diseases. Growing evidence both from observational and biological sources support the hypothesis that eating disorders share the feature of inducing an alteration in the reward system, which plays a central role in instinctual drives, including the drive to eat. On the observational plane, the involvement of the reward system in eating disorders is supported by the fact that eating disorder-related symptoms resemble those typically endorsed by individuals with substance use disorders. In the latest version of the Diagnostic Statistic Manual it is stated that this re-

L. Rovai et al.: The role of the opioid system in Eating Disorders. Perspectives for new treatment strategies

semblance may reflect the involvement of the same neural systems in the two groups of disorders, but the lack of any clinical evidence to support this theory has precluded the inclusion of eating disorders in the category of addictive disorders [1]. On the biological plane structural and functional alterations in reward circuits have been hypothesized as inducing a predisposition to develop an eating disorder in response to malnutrition or repeated binge eating and purging [11, 42, 43, 141]. In developing this hypothesis, a few authors have investigated the predictive value of various biomarkers in anorexia nervosa and bulimia. Both disorders have exhibited an increase in the grey matter volume of the medial orbitofrontal cortex. Antero-ventral insula grey matter volumes have been shown to have risen on the right side in anorexia nervosa patients, and on the left side in patients suffering from bulimia nervosa, compared with healthy controls. Anorexic and bulimic patients present two patterns of biomarkers that seem to be mutually exclusive [42]. This dichotomy has also been confirmed by temperamental and personological measuring scales (Temperament and Character Inventory and Tri-dimensional Personality Questionnaire). Anorexic and bulimic patients have shown alterations in their sensitivity to reward that place them in opposition to each other. In general, patients with a form of anorexia nervosa belonging to the restricting type have reported having become less sensitive to reward than healthy controls, whereas patients with bulimia nervosa and anorexia nervosa – of the binge/purging type – reported having become more sensitive. Both groups of patients have shown a higher sensitivity to punishment than healthy controls [60]. In summary, the sensitivity of dopamine reward pathways has been implicated in the risks arising from eating disorders, but the evidence is divided on the issue of the direction of causal association. One argument is that a Reward Deficiency Syndrome is the risk factor, while others contend that hypersensitivity to reward enhances the motivation for pleasurable activities like eating, in such a way that those activities become addictive. In this review we will focus on Anorexia Nervosa, Bulimia, and Binge Eating Disorder, as these three disorders are those in which the involvement of the reward system has been most accurately defined. 1.3.1. Reward activity in anorexia nervosa

Anorexia nervosa is associated with a fear of weight gain and the refusal to maintain a minimally

normal body weight [1]. Individuals with anorexia nervosa are often described as possessing excessive self-control and are unusual in their ability to reduce or eliminate the consumption of palatable foods, a behaviour that suggests disturbances in reward processing [15]. Both animal and human studies assessing mechanisms of self-starvation under conditions of stress and diet have proposed a central role for the mesolimbic reward system in the maintenance of the core symptoms of anorexia nervosa [41]. Structural imaging studies on clinical samples have demonstrated brain tissue abnormalities in anorexic patients, the most important being a global reduction in grey and white matter, and decreases in reward and somatosensory regions [148]. All these biological observations are consistent with the hypothesis that, in anorexic patients, reward has been linked to reduced food intake and excessive exercise, so that while patients' pathological behaviours are initially rewarding, they become reinforced in a pathological manner that turns out to be punishing [81]. The impaired ability to experience taste-related pleasure, shown by anorexic patients, may thus reflect the altered motivational role of weight loss rather than an impaired ability to experience reward [33, 82]. Some authors have focused on the increased capacity to delay reward of anorexic individuals, as a condition putatively involved in the maintenance of food restriction. Patients suffering from anorexia nervosa have shown a tendency to delay receipt of a monetary, non-food related reward – a parameter suggestive of enhanced self-control that may go beyond food consumption. It is notable that this psychological profile is the opposite of that of substance abusers, who are well known for their incapacity to delay reward [142]. Other authors have focused on the hyperactivity of patients with anorexia nervosa. The link between restricted food intake and an increase in physical activity is very likely to bring an evolutionary advantage which, initially, tends to be both functional and rewarding. In anorexia nervosa this paradoxical reward of hyperactivity has been hypothesized to be an expression of the neurobiological changes that may underlie the development of the disorder [132]. Regardless of the problem of identifying the ‘primum movens’ of anorexia nervosa, neural overlap between reward and punishment circuits has been put forward as the most likely explanation of the difficulties shown by these individuals in differentiating between positive and negative eating-related feedbacks - 17 -


[153]. 1.3.2. Reward activity in bulimia nervosa

Bulimia nervosa is associated with recurrent episodes of binge eating in which the subject eats a large amount of food and experiences a sense of lack of control. These episodes are followed by inappropriate compensatory behaviours that aim to prevent weight gain, such as self-induced vomiting, misuse of laxatives, diuretics, or other medications, fasting or excessive exercise. These subjects’ self-evaluation is unduly influenced by body shape and weight [1]. The impact of alterations to reward processing have also been implicated in bulimia nervosa. The specific eating patterns of bulimic patients show a closer resemblance to the behavioural patterns of substance abusers than to those of anorexic patients, and are thought to be particularly addictive. Binge eating and purging with intermittent dietary restriction could, through their effects on the dopaminergic system, enhance the motivational role of food, especially in individuals who are particular sensitive to reward [149]. Both neurobiological and psychological evidence support the view that bulimia nervosa functions in an addictive way. A neurobiological study has investigated the functional magnetic resonance patterns of women with full and sub-threshold bulimia nervosa, the main result being the abnormal neural activation that is displayed in response to food intake and anticipated food intake. It is probable that this altered response pattern to food-related reward is the result of a history of binge-eating highly palatable foods [19]. Responsiveness to reward has been studied in unmedicated bulimic subjects in remission, in some cases by means of pharmacological catecholamine depletion. This experimental procedure has uncovered a dopamine–related disturbance of the central reward processing systems which might reflect a trait-like deficit that aggravates vulnerability to bulimia nervosa [54]. As in the case of anorexia nervosa, an altered striatal response with neural overlapping between reward and punishment processing has been put forward to explain difficulties in discerning the emotional significance of a food-related stimulus [152]. Moving on now to the psychological plane, bulimic patients have mostly shown a cyclothymic temperament, a construct that is closely related to impulsivity and sensitivity to reward, and is thought to predispose to substance abuse. This psychological profile seems to some extent to be the opposite of that - 18 -

of anorexic patients, who have a low sensitivity to reward and show a great ability to delay food-related rewards [5]. 1.3.3. Reward activity in binge eating disorder

Binge eating disorder is associated with recurrent episodes of binge eating in which the subject quickly eats large amounts of food even if not physically hungry. The binge eating episodes, which are dominated by feelings of disgust and embarrassment, are to some extent similar to those of bulimic patients, except for the lack of compensatory behaviours, which are typically absent in binge eating disorder [1]. On the neurobiological plane, a functional magnetic resonance imaging study, by exploring the neural correlates of visually induced food reward, has made it clear that patients suffering from binge eating disorder present different forms of brain activation in response to visual food stimuli from those of patients suffering from bulimia nervosa. Both groups experienced the food pictures as very pleasant; the first group reported enhanced reward sensitivity, whereas the second group of patients displayed greater arousal [133, 157]. Given the hypothesized link between dopamine receptor subtypes and reward sensitivity, some authors have assessed the role of those alleles whose expression was a reduced dopamine receptor density, but the results are controversial [35]. Moving to the field of experimental psychology, monetary reward processing has been studied in obese individuals with and without binge eating disorder. Patients suffering from binge eating disorder have performed a monetary reward/loss task that is significantly different from that of other obese patients, as analysed by means of functional magnetic resonance imaging [14]. 1.4. The role of opioid system in eating disorders If we intend to study the involvement of the reward system in the pathogenesis of eating disorders, it is of primary interest to explore the role of the opioid system, not only because of its neurobiological primacy, but also because of its close links with feeding behaviours and metabolic regulation [74]. 1.4.1. Opioid activity in anorexia nervosa

With reference to neurobiological factors, higher levels of cerebrospinal fluid opioid activity have been found in patients with anorexia nervosa who were severely underweight. This disposition might be


a compensatory response to weight loss or might be aetiologically related to anorexia nervosa [80]. On genetic grounds, changes in the serotonergic and opioidergic neurotransmitter system are among the other developments observed in people suffering from anorexia. In particular, the genes for serotonin and opioid-delta receptors have been found in a region identified in a linkage analysis, and have been discussed in attempts to explain the aetiology of anorexia nervosa [17, 18]. Moving from humans to animals, an atypical endogenous opioid system in mice has been related to an autoaddiction opioid model of anorexia nervosa, where the responsiveness of the opioid system is thought to play a predisposing role in the development of the disease. Morphine-mediated activation of the endogenous opioid system increases food intake and causes sedation in most species, including normal humans and rats. By contrast, in mutant mice, morphine causes anorexia and hyperactivity, in a way similar to what can be observed in anorexia nervosa patients [103]. From an evolutionary point of view, anorexia nervosa may be a pathological consequence of the triggering of a primitive mechanism for coping with unforeseen food shortages. This mechanism would lead to the short-term ability to mask a depressed state related to food depletion, especially thanks to the relationships that link the endogenous opioid system with other systems, such as the dopaminergic, noradrenergic and hormonal ones [73]. 1.4.2. Opioid activity in bulimia nervosa

On neurobiological grounds, regional μ-opioid receptor binding in the insular cortex has been found to be weaker in bulimic patients than in controls, and to inversely correlate with fasting behaviour. In the light of this observation it has been hypothesized that the abnormal, recurrent activation of this system may constitute a neural substrate for the maintenance of the self-perpetuating behavioural cycle of bulimic subjects, as the insula is the primary gustatory cortex, and has often been implicated in the processing of the reward value of food [16]. An animal model of bulimia nervosa, based on opioid sensitivity to fasting episodes, has been considered too. A group of female rats have been deprived and maintained at 75-80% of normal body weight at three different stages of their development. Following recovery to normal weight, food intake was measured with and without butorphanol tartrate, a κ-σ agonist. Animals with a history of deprivation showed an in-

crease in post-recovery feeding when they were tested at normal body weight and were not deprived of food. More importantly, butorphanol had the effect of prolonging food intake only in the rats that had a developmental history of food restriction. One possible explanation for this is that a developmental history of fasting in eating disorders may trigger changes in opiate systems that result in atypical feeding behaviour in the adult [57]. 1.4.3. Opioid activity in binge eating disorder

On neurobiological grounds, both the nucleus accumbens and amygdala are thought to participate in the control of opioid-mediated food intake, during binge episodes. As a matter of fact, the intra-accumbens administration of the μ-opioid encephalin agonist is followed by a substantial increase in the intake of fat, while this increase has shown to be completely blocked by the concurrent inactivation of either the basolateral or the central nucleus of the amygdala, by means of a GABA agonist. A possible explanation is that amygdala inactivation reduces the hedonic properties of high-fat palatable food [158]. In animal models of binge eating, selective μ-opioid receptor antagonists have been shown to suppress food consumption. In humans, non-selective opioid receptor antagonists have shown the property of reducing hedonic taste preferences and food intake, particularly in the case of palatable foods, and to cause short-term weight loss. These effects have been linked to the negative modulation of dopamine release within the reward circuitry. The suggestion is that the reduction of the μ-opioid receptor-mediated hedonic and motivational processes that drive the consumption of highly palatable foods may be a promising therapeutic approach for obesity and binge-eating disorder [46, 117]. 1.5. Opioid medications Opioids are drugs that have similar effects to opium, a substance that has been used by mankind for thousands of years because of its therapeutic (analgesic, sleep-inducing, anti-diarrhoeal) and recreational (euphoric) properties. A number of drugs, such as morphine, codeine, papaverine, and thebaine, are derived from papaver somniferum, the plant that is used to prepare opium [3, 68, 69]. Opioid agents are generally classified as agonists or antagonists according to their intrinsic activity on each kind of receptor. The overall effect of an opioid agent depends on its activity on each single - 19 -


type of receptor; some opiates act as agonists on one type and antagonists or partial agonists on another. The potency of an opioid agonist depends on 1) the affinity of the agonist for the receptor, that is, its tendency to bind to the receptor; and 2) the efficiency of the agonist, also called ‘intrinsic activity’, that is, its ability, once it is bound to the receptor, to induce a series of changes that lead to the entire range of pharmacological effects. Full agonists have maximal efficiency and produce similar effects to those of endogenous opioids, whereas partial agonists have intermediate efficiency and produce sub-maximal effects, compared with those of endogenous opioids [64, 104, 105].

μ and κ opioid receptors, and medium affinity for δ opioid receptors. As to functional activity, the drug behaves as a moderately potent δ-opioid antagonist, as a potent κ-opioid partial agonist, and as a μ-opioid antagonist. Nalmefene is extensively metabolized, and has a plasma half-life of almost 11 hours, compared with 60-90 min for naloxone. It has been shown to reverse opioid intoxication for as long as 8 hours, reducing the need for continuous monitoring of intoxicated patients and repeated dosing with naloxone. Mainly used in the treatment of interstitial cystitis and chronic alcohol dependence, its long duration of action facilitates extended withdrawal reactions in chronically opioid-dependent patients [47, 155].

1.5.1. Naloxone

1.5.4. Buprenorphine–naloxone

Naloxone is a μ-opioid receptor competitive antagonist which, thanks to its extremely high affinity, displaces the opioid peptides that are related to receptors (whether endogenous or exogenous) and produces a rapid neutralization of their effects; in the case of dependent patients, this leads to the onset of a withdrawal syndrome. Naloxone has a 60-90 minute half-life, and its most widespread use is the treatment of respiratory depression in the context of an opiate overdose. It also has an antagonist action, though with a lower affinity, at the sites of κ- and δ-opioid receptors [72, 104, 126, 164].

The combination buprenorphine-naloxone has been developed to reduce the potential for abuse and limit the grey market for oral buprenorphine; it brings together a μ-opioid partial agonist and a δ and κ-antagonist. If the combination is taken sublingually, naloxone is absorbed to a negligible extent, and thus has no significant effect, but if it is used intravenously in subjects tolerant to opiates, the antagonist naloxone can produce an acute but not life-threatening withdrawal syndrome [10, 56, 58, 137].

1.5.2. Naltrexone

Naltrexone is an opioid receptor antagonist used primarily in the treatment of alcohol dependence [121, 129] and pathological gambling [20], and secondarily in the management of opioid dependence, especially where opioid agonists are not available. Naltrexone is commonly used as an anti-reward medication, and should not be confused with naloxone. Using naloxone in place of naltrexone can cause acute opioid withdrawal symptoms; conversely, using naltrexone in place of naloxone in an overdose can lead to insufficient opioid antagonism and fail to reverse the overdose. Naltrexone and its active metabolite 6-β-naltrexol have half-lives of 4 hours and 13 hours, respectively, and both are competitive antagonists at sites of μ- and κ-opioid receptors, and, to a lesser extent, at sites of δ-opioid receptors [52, 104, 126, 139]. 1.5.3. Nalmefene

Nalmefene is a selective opioid receptor ligand without any significant affinity to targets apart from opioid receptors. With respect to the opioid receptor subtypes, nalmefene has an equally high affinity for - 20 -

1.5.5. Buprenorphine

Buprenorphine is a synthetic, fat-soluble drug, acting as a partial agonist at the μ-opioid receptor and on opioid-like receptors, and exerting a not univocal but mainly antagonist action on δ and κ-opioid receptors. It has greater affinity and less intrinsic activity than full agonists such as methadone, morphine or heroin. This means that buprenorphine displaces the other agonists from the receptor, but, in the short term, does not produce an effect equivalent to that produced by higher dosages of other agonists that have greater intrinsic activity. Because of this discrepancy, buprenorphine may produce withdrawal symptoms when there is an initial situation of opioid tolerance induced by a full agonist, but it makes it possible to achieve blockade effects in subjects with low tolerance to opioid agonists. Although buprenorphine is an opioid, and thus can produce typical opioid agonist effects and side-effects such as euphoria and respiratory depression, its maximal effects are less than those of full agonists like heroin and methadone. The agonist effects of buprenorphine rise linearly with increasing doses of the drug, until at moderate doses they reach a plateau, and no longer continue to increase as doses are raised. This is called a ‘ceiling effect’, whose


main benefit is the lower risk of side-effects and overdose, compared with full opioid agonists. Because of its poor oral bioavailability, buprenorphine formulations for opioid addiction treatment are distributed in the form of sublingual tablets. Buprenorphine is highly bound to plasma proteins, and is metabolized by the liver via the cytochrome P4503A4 enzyme system into nor-buprenorphine and other metabolites. Its half-life is 24-60 hours. The maximal effects of buprenorphine appear to occur at a 16 mg dose. The only probable effect of higher doses is higher levels of opioid receptor blockade, without the higher doses inducing any substantial increase in buprenorphine’s intrinsic activity [75, 87, 144-147]. 1.5.6. Methadone

Methadone was the first opioid agonist to be made available for the treatment of patients with opiate addiction. It is a synthetic drug that acts on the same receptors as heroin (μ) and has a similar affinity with them. Methadone is usually taken orally, and is rapidly absorbed through the gastrointestinal mucosa, with a bioavailability ranging from 40 to 100%. The onset of its effects takes place within 30' after oral intake, with a peak after an average of 2.5 hours. The plasma concentrations increase in the first 3-4 hours after oral intake and then gradually decline. Methadone has a slow metabolism and a very high fat solubility, making it longer lasting than morphine-based drugs. It has a typical elimination half-life of 15 to 60 hours, with a mean of around 22, but metabolism cycles vary greatly between individuals, up to a factor of 100, ranging from as few as 4 hours to as many as 130 hours, or even 190 [2, 12, 13, 39, 59, 162]. Aims

A wide corpus of neurobiological evidence suggests that eating disorders share an addictive nature, with the opioid system playing a central role in their pathogenesis and maintenance. With this hypothesis as starting point, we intend to: • Take into account the past and current literature on the epidemiological and clinical correlation between opioid use disorder and eating disorders. • Study the action displayed by opioid medications on feeding behaviours and eating disorder symptoms. • Speculate whether opioid medications can be used in the management of eating disorders, especially anorexia nervosa, bulimia nervosa and binge eating disorder.

• 2.

Speculate whether opioid medications can be used in the management of eating disorders. Methods

In order to shed light on the epidemiological and clinical correlation between opioid use disorder and eating disorders, we carried out a thorough search on the “Scopus data base”, to find papers whose title contained the terms “heroin”, “opioid” and “opiate”, matched with the terms “eating”, “feeding”, “anorexia”, “anorexic”, “bulimia”, “bulimic”, and “binge eating”. In order to recover the history of the actions displayed by opioid medications on feeding behaviours and eating disorders symptoms, we searched for the terms “opioid”, “methadone”, “buprenorphine”, “buprenorphine-naloxone” “nalmefene” and “naltrexone”, matched with the terms “eating” and “feeding”. We followed up by comparing the risk-benefit ratio of opioid medications with that of medications traditionally used in this class of diseases. 3.

Results

3.1. Heroin addiction and eating disorder comorbidity 3.1.1. Epidemiological data

In the literature there is a low level of availability of data about comorbidity between addictive and eating disorders. Most of the studies that have examined this comorbidity of heroin addicts have pointed to bipolar spectrum disorders as the most frequent form of comorbidity in such patients [98, 100], while eating disorders have been shown to have only a marginal position. In a population of young heroin users recruited from outside the healthcare context, and resident in Barcelona, Spain, psychiatric comorbidity has been evaluated with the “Psychiatric Research Interview for Substance and Mental Disorders semi-structured interview”. Around two-thirds of the sample had lifetime psychiatric comorbidity, with antisocial personality and mood disorders being the most frequent conditions (33% and 26%, respectively). Eating disorders, which were, as expected, less frequent than affective diseases, were more common among women than men [127]. DSM-IV lifetime and current psychiatric comorbidity has also been assessed in 404 consecutive patients with binge eating disorder (BED), by means of semi-structured diagnostic and - 21 -


clinical interviews. Overall, 73.8% of patients with BED had at least one additional lifetime psychiatric disorder and 43.1% had at least one current psychiatric disorder. Lifetime-wise, mood (54.2%) and anxiety (37.1%) disorders were the most common form of comorbidity, while substance use (24.8%) disorders were ranked in third place, and were, as expected, more frequent in men [53]. Interestingly, among anorexic nervosa patients, those who shared a lifetime history of bulimia nervosa showed the highest rate of substance use disorders [128]. 3.1.2. Clinical data

In the literature there is a substantial lack of data about the clinical features of patients suffering from comorbid eating and substance use disorders. 3.2. Opioid antagonist in anorexia Only a few studies have examined the therapeutic usefulness of opioid blockade in anorexia, and the findings are disappointing. On the basis of the autoaddiction model proposed for anorexia nervosa, naltrexone has been administered to outpatient subjects suffering from various subtypes of anorexia nervosa and bulimia nervosa, in a double-blind clinical trial with randomized cross-over designs. Reduction in binge/ purge symptomatology was evident in the naltrexone period over placebo for 18 out of 19 subjects with either bulimia or anorexia nervosa of the bulimic subtype. No therapeutic response was shown by anorexic subjects of the restricting subtype [91, 102]. Opioid blockade has been shown to be ineffective even on endocrinological manifestations of anorexia. A study has tried to determine whether chronic treatment with naltrexone can increase luteinizing hormone (LH) and follicle-stimulating hormone (FSH) secretion in women with hypothalamic amenorrhea, anorexia nervosa, and polycystic ovarian disease. A significant increase in the LH pulse frequency was observed in patients with hypothalamic amenorrhea and polycystic ovarian disease, but not in anorexic patients [9]. Some evidence from clinical settings even suggests that opioid blockade could have a negative effect on the feeding behaviours of psychiatric patients. It is striking that, when a severe obsessive-compulsive male patient was successfully treated with naltrexone, symptoms resembling those of anorexic patients occurred [44].

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3.3. Opioid antagonist in bulimia Evidence gathered on the usefulness of opioid blockade in bulimic patients is more comforting [76, 78]. As reported above, naltrexone has proved to be effective in reducing the binge/purge symptomatology, not only in bulimic patients, but also in those suffering from anorexia nervosa of the bulimic subtype. When a detailed longitudinal analysis conducted over a 16-month period was performed on a bulimic subject from that study, it emerged that the therapeutic response included multiple parameters such as binges, purges, urges to perform both behaviours, eating patterns, emotional states, and “Eating Disorder Inventory” questionnaire scores [102]. The effectiveness of naltrexone in bulimia nervosa has also been tested in combination with fluoxetine, which can be considered a more conventional treatment for this disease. Four patients matching DSM-IV criteria for bulimia nervosa were treated in a crossover trial with naltrexone alone, fluoxetine alone, and a fluoxetinenaltrexone combination. Three patients presented a complete remission when treated with the fluoxetinenaltrexone combination [96]. In line with these observations, the use of naltrexone has been successfully studied in ten individuals with antidepressant-resistant bulimia. Seven of the ten experienced at least a 75% reduction of their bulimic symptoms, and maintained their improvement throughout the three to five month follow-up [77]. With regard to the use of naltrexone in bulimic patients, the evidence is not uniform. In a placebo-controlled, double-blind crossover study, 16 normal-weight bulimic women were treated in an outpatient setting with low-dose naltrexone and placebo. The use of the active drug was not associated with a clinically significant reduction in binge eating or vomiting episodes [114]. It should, however, be borne in mind that this result could be due to the low dosages used, as may be concluded from a study of low-dose versus high-dose naltrexone. Sixteen bulimic patients consented to a 6-week trial of naltrexone, receiving either standard daily dosages of 50-100 mg or high daily dosages of 200-300 mg. At the end of 6 weeks, there were no significant changes in the frequency of binge eating or purging in individuals in the low-dose group, whereas those in the high-dose group displayed significant reductions in both behaviours. Moreover, four individuals in the low-dose group who crossed over to high-dose naltrexone at the end of the study went on to experience significant reductions in binge eating and purging. On one hand these findings document the potential advantages of


opiate blockade in treating bulimia, and, on the other, suggest that dosages of naltrexone greater than those needed to block exogenous opiates may be required for therapeutic efficacy in reducing binge eating and purging [79]. 3.4. Opioid antagonist in binge eating Opioid antagonism has also proved to be of some interest in cases of binge eating disorder, in line with its partial clinical overlapping with bulimia nervosa. A paper has measured the effects of a single intracerebroventricular dose of nor-binaltorphimine, a specific and long-lasting κ opioid antagonist, on food intake, body weight, and satiety measures in an animal model of binge eating disorder. The analysis of individual human subjects revealed a differential response to opioid antagonism, with some responding and others responding poorly. These data suggest that lessened sensitivity to opioid antagonists or increased central dynorphin levels may contribute to the hyperphagic eating pattern observed in the obese Zucker rat [71]. A randomized, placebo-controlled, flexible dose, pilot study has preliminarily assessed the effectiveness of a novel opioid antagonist, ALKS-33, in 62 outpatients with binge eating disorder. No significant differences emerged between treatment groups in binge eating episode frequency or any other measure of binge eating, body weight, or eating pathology, the main conclusion being the ineffectiveness of ALKS33 on binge eating disorder, at least when administered daily for 6 weeks [106]. Another paper has studied, in a double-blind parallel group design, the effects of the μ-opioid receptor antagonist GSK1521498 on hedonic and consummatory eating behaviours in a sample of 63 binge-eating obese subjects. GSK1521498, at two different dosages, was no different from placebo in its effects on weight, fat mass and binge eating scores. However, compared with placebo, at the higher dosage it caused a significant reduction in hedonic responses to sweetened dairy products and reduced calorific intake, particularly of high-fat foods during ad libitum buffet meals. These findings further support the clinical significance of μ-opioid receptor blockade in binge-eating obese subjects [25, 165]. A growing interest has recently been directed to the new μ-opioid receptor antagonist nalmefene, which has proved to decrease meal size, food and water intake and weight gain in animal models of binge eating. In obese male rats, nalmefene led to a fall in the size of the first meal after a 10-hr fast and reduced general food intake, with a long-lasting action. Administra-

tion of nalmefene daily for 7 days decreased average meal size and daily food intake, while increasing meal frequency. Feeding responses on day 7 were similar to those on day 1, suggesting a lack of development of tolerance. Food and water intake and weight gain during a 3-week treatment period were reduced more in lean rats by low doses of nalmefene and more in obese rats by higher doses of nalmefene [109, 110]. The synergistic effects of nalmefene and cannabinoid inverse agonist AM251 on food intake have been demonstrated in mice. This pharmacological association has proved to determine a significant fall in food intake in both lean and diet-induced obese mice; this supports the idea of a synergistic interaction between opioid and cannabinoid systems in regulating feeding behaviour [27]. Nalmefene has been shown to suppress appetite in humans, but its effects on chronic food intake and body weight are still unclear. A paper has reported that chronic (21-day) oral administration of nalmefene at 2 or 10 mg/kg/day in diet-induced obese mice leads to significant increases (9-11%) in cumulative food intake. Mice in the nalmefene-treated groups also gained body weight at a rate faster than that of the control group. Body composition analysis showed that the extra body weight gains in the treated animals were mostly due to increased fat accumulation. Since acute nalmefene treatment showed a trend towards a decrease rather than an increase in food intake, it is possible that the chronic administration of nalmefene leads to increased food intake and body weight gain. Pharmacologically active metabolites rather than the drug itself might cause the orexigenic effect of nalmefene. This result argues against the potential use of nalmefene for treating human obesity [26]. 3.5. Opioid partial agonists in eating disorders? Opioid partial agonism has been studied in the context of feeding behaviours, with special attention directed to buprenorphine, which has been shown to increase the intake of freely available and operant-contingent food in satiated rats. In particular, buprenorphine produced a significant increase in short-term free feeding, an effect enhanced by repeated administration. In operant responding mice, buprenorphine decreased latency, so initiating responding to food, and increased the total number of pellets consumed in a 1-h session. Increases in food intake relative to controls were caused by continued responding to food as the sessions progressed. Naloxone suppressed both the free-feeding and operant-contingent intake - 23 -


induced by buprenorphine [131]. In another animal study, the effects of naloxone and three oripavine derivatives – diprenorphine, an antagonist, buprenorphine, a mixed agonist-antagonist, and etorphine, an agonist – were examined on food-reinforced responding in squirrel monkeys. A 12-min period of unpunished responding was made to alternate with a 4-min period in which each response produced a brief electric shock to the tail. Responding in the two components was not differentially affected by any of the drugs. Naloxone decreased responding in both components, but only slightly at high doses. In contrast, the three oripavines produced prominent dose-related decreases in responding, with the following order of potency for the non-punishment components: etorphine showed greater potency than buprenorphine, which in its turn showed greater potency than diprenorphine. Although all three oripavines produced comparable decreases in food-reinforced responding, different mechanisms have been hypothesized for the antagonists, compared with full and partial agonists [37]. The effects of buprenorphine on feeding behaviours have also been studied in Macaque monkeys. Low acute doses of buprenorphine (0.01 and 0.03 mg/kg) did not change the number of food pellets earned, while the acute administration of high doses (0.10 and 0.30 mg/kg) of buprenorphine significantly suppressed food-maintained responding. Chronic buprenorphine self-administration (0.01-0.10 mg/kg/ injection) did not significantly suppress food intake, even at total daily doses that were 3 to 9 times higher than the highest dose (0.03 mg/kg) studied in the acute pre-treatment paradigm. These data suggest that during the chronic self-administration of buprenorphine, the acute suppressive effects on food-maintained responding are dose-dependent and subject to tolerance phenomena [111]. In order to understand to what extent the effects displayed by opioid agents on feeding behaviours are affected by tolerance phenomena, some authors have studied the changes appearing in rats in the progression of food-maintained responding over time, following chronic buprenorphine or methadone administration. Seven lever-pressed rats were subjected to a schedule of food presentation, with the number of responses per reinforcer systematically increasing during each session. Break point (the number of responses before session termination) was measured. Both drugs initially eliminated the progression of rats' food-maintained responding. Break points during chronic methadone administration did not return to baseline levels after 80 drug sessions and a dose re- 24 -

duction. In contrast, break points during chronic buprenorphine administration were considerably above baseline control levels for two rats and returned to baseline levels for the third [92]. Rats seem to develop tolerance to the effects of buprenorphine, but not to those of methadone, on feeding behaviours. Other authors have investigated the effects of chronic buprenorphine treatment on cocaine and food selfadministration by six rhesus monkeys. Cocaine selfadministration decreased significantly and remained 60 to 97% below baseline levels throughout 120 days of buprenorphine treatment. After the substitution of saline for buprenorphine, cocaine self-administration resumed. Food self-administration was initially reduced (P less than .01-.05), but tolerance to buprenorphine's suppression of food-maintained responding developed over 30 to 70 days of treatment. Food selfadministration returned to and significantly exceeded treatment baseline levels, whereas cocaine self-administration remained significantly suppressed [112]. 3.6. Opioid agonist in eating disorders? A variety of opioid agents are known to increase short-term food intake. Among opioid medications, a series of studies has focused on methadone. In particular, the effect of methadone on free feeding has been measured in satiated rats for 3 consecutive days. Two hours after methadone administration, food intake was inversely related to dose, but after 6 h a direct relationship between dose and feeding was obtained. Food intake increased with repeated methadone administration, with maximal scores occurring in the third and fourth hours after methadone administration. These data indicate that methadone stimulates short-term feeding in satiated rats. The apparent paradox of methadone is that the increase in food intake is associated with a fall in food-reinforced operant responses, both in free feeding studies and in operant chambers [130]. Some authors have studied the effects on rhesus monkeys of chronic methadone treatment on cocaine- and food-maintained responding. During saline treatment, cocaine maintained a dosedependent increase in the number of cocaine injections per day, and monkeys usually responded to the maximum number of pellets. Methadone decreased cocaine self-administration in a dose-dependent way, with variable effects on food-maintained responding. Methadone produced a dose-dependent, non-selective decrease in the progression of both cocaine and food intake. These observations provide evidence suggesting that methadone non-selectively lowers rates of


operant responding, both in the case of food and in that of cocaine [118]. 4. Discussion 4.1. Heroin addiction and eating disorder comorbidity In this paper we raise the question of whether opioid medications should be part of the pharmacotherapy of eating disorders. We have found a low availability of epidemiological data regarding the correlations between opiate addiction and eating disorders, and a substantial lack of data on the clinical features of these correlations. Eating disorders seem to occupy a marginal position among the comorbid disorders shown by heroin addicts; on the other hand, substance abuse disorders and eating disorders share a high rate of comorbidity with bipolar spectrum conditions [98, 100, 116, 123]. This convergence strengthens the case for there being a bipolar connection between the two diseases, which would then play the role of general diathesis to the pathologies of the reward system. 4.2. Anorexia The search for an effective psychopharmacological strategy in treating anorexia nervosa has been inconclusive for decades, and several medications have been unsuccessfully evaluated, ranging from typical and atypical antipsychotics to mood stabilizers, and antidepressants, too. What emerges is the lack of a standard protocol for pharmacotherapy trials in patients with bulimia nervosa and anorexia nervosa [115]. With regard to antipsychotic medications, their use in anorexia nervosa is only partially supported by clinical evidence. A systematic review assessing the effectiveness of antipsychotic medication for improving behavioural symptoms of anorexia nervosa has included data from four randomized controlled trials, concluding that there is insufficient evidence to either support or refute the use of antipsychotic medication in anorexia nervosa [32]. Another systematic review and various meta-analyses have estimated the influence of atypical antipsychotics on body mass index, eating disorder, and psychiatric symptoms in individuals with anorexia nervosa. Compared with placebo, atypical antipsychotics turned out to be associated with a less than significant increase in body mass index and a less than significant effect on the drive for

slimness and bodily dissatisfaction. The outcome of these studies was that the medications tested led to an increase in anxiety and overall eating disorder symptoms [88]. The use of risperidone has been tested in a double-blind, placebo-controlled study for the treatment of adolescents and young adults with anorexia nervosa [61], while olanzapine, in four randomized clinical trials, has shown superiority to placebo, chlorpromazine, and aripiprazole in terms of weight gain and reduction of obsessional symptoms [22]. With regard to antidepressant medications, a retrospective study assessing the effects of SSRI treatment in partially weight-restored children and adolescents with anorexia nervosa, has revealed that, despite evidence of an altered serotoninergic function [23], SSRIs do not significantly influence body mass index, core eating disorder symptoms, depression, or obsessive-compulsive scores [62]. With regard to mood stabilizers, a double-blind controlled trial has evaluated the effectiveness of lithium carbonate in anorexia nervosa. In a 4-week period, eight young women with primary anorexia nervosa were evaluated for the effects of lithium carbonate administration, while eight patients were treated with placebo and served as a control group. Group differences appeared in the areas of "denial or minimization of illness" on the "selective appetite", and on weight gain, especially at weeks 3 and 4 [55]. In summary, of all the medications studied for the treatment of anorexia nervosa, only lithium carbonate has proved to be effective both on the physical and the psychic measurement scales. The use of neuroleptics is controversial, while that of antidepressants has turned out to be fruitless. If we look at opioid medications, on one hand there are opioid antagonists that have been shown to be useless in anorexic patients, as would be expected from the low sensitivity to reward that is typical of these patients. On the other hand there are full and partial agonists, which seem to present interesting properties such as that of increasing free food intake, and decrease food-reinforced operant responding, at least in animal models. More specifically, these effects are dose-dependent, and are liable to tolerance phenomena only in the case of buprenorphine, while methadone maintains its action unchanged, even in chronic administration. Both full and partial agonists offer the additional advantage of being known to possess all the pharmacological properties (mood-stabilizing as well as antipsychotic) that can be accredited to the medications commonly used in treating anorexia. - 25 -


The mood-balancing properties of opioid agents that have emerged in clinical settings have been further documented by the long-term outcomes of heroin dependent, treatment-resistant patients with bipolar I comorbidity under enhanced methadone maintenance. When dual diagnosis heroin addicts have been compared with non-dual diagnosis peers by means of the “Global Clinical Impression” scale and DSM-IV criteria, the best clinical outcomes were observed in patients suffering from bipolar disorder [95]. The mood-stabilizing property of opioid agents is supposed to be useful in anorexic patients, considering the high rate of comorbidity with bipolar spectrum disorders that has been recorded for them [116, 123]. Opioid full and partial agonists have also been shown to possess antipsychotic properties, as suggested by the low frequency of psychotic spectrum disorders in heroin-dependent patients, or those in methadone treatment programmes [138]. As a matter of fact, a psychotic episode can occur, in previously psychotic patients, after rapid discontinuation of methadone or buprenorphine [30, 89, 138, 156]. In addition, when combined with methadone, low dosages of traditional antipsychotics are needed to control the psychotic symptoms of heroin addicts who have been hospitalized for an acute psychotic episode [94, 99, 122]. On the pharmacological plane, opiate agonists are known to induce acute neuroleptic-like effects on the endocrine system, such as hyperprolactinemia and the suppression of surrenal activity, so suggesting an antidopaminergic activity. This property has been well documented in the case of methadone, whose administration is followed by an increase in serum prolactin [29, 48, 151]. Similar properties have been found for buprenorphine, in line with the psychotomimetic properties shown by selective kagonists such as pentazocine [63, 70, 97]. As a matter of fact, buprenorphine has been shown to be active against hallucinations and delusions over a time-span of four hours in a small group of heterogeneous psychotic patients [134]. In summary, opioid full and partial agonists seem to present a promising profile of effects that could prove to be useful in treating anorexia nervosa. These compounds enhance food intake while displaying all the pharmacological properties presented by the most commonly used medications, with the advantage that they interact with the reward system in a stabilizing rather than blocking manner. Methadone seems to be the most promising, as its actions on feeding behaviours are not subject to tolerance phenomena; at the same time it has more handling - 26 -

problems and more side-effects than buprenorphine. For these reasons we speculate that it could be used in anorexic patients that have proved to be resistant to buprenorphine. Conversely, buprenorphine might be useful to patients who, while having a milder eating disorder symptomatology, present a comorbid bipolar disorder that would benefit from the anti-dysphoric action of k-antagonism. 4.3. Bulimia To date, bulimia nervosa appears to be a disease that is easier to treat than anorexia nervosa. Several drugs have been successfully tested, ranging from antidepressant to mood-stabilizing medications. With regard to antidepressant drugs, tricyclics, monoamine oxidase inhibitors, and selective serotonin reuptake inhibitors have been documented to reduce bulimic symptoms [50]. A randomized, double-blind, placebo-controlled, multicentre study of short-term and long-term pharmacotherapy of bulimia nervosa has identified fluvoxamine, among serotoninergic agents, as a possible candidate for the treatment of bulimic subjects [135]. Other authors have focused on fluoxetine. A multicentre, doubleblind, randomized clinical trial of placebo, 20 mg of fluoxetine, and 60 mg of fluoxetine for 8 weeks, has assessed clinically significant attitudinal changes in 382 women suffering from bulimia nervosa. Behavioural changes were measured using self-monitored measurement scales for binge eating and purging, and psychological changes were measured with the “selfrating Eating Disorder Inventory” and the “Hamilton Rating Scale for Depression”. In the short-term, the treatment of bulimia nervosa with fluoxetine has been shown to produce clinically significant attitudinal and behavioural changes. These effects observed on attitudinal changes were unrelated to the presence of depression at baseline [49, 50]. Among mood stabilizers, both lithium carbonate and anticonvulsant drugs have been tested. With regard to anticonvulsants, lamotrigine and carbamazepine have been compared, in association with fluoxetine, on 45 bulimic patients. Both combinations allowed a marked, stable improvement in the patient's state. Lamotrigine, compared with carbamazepine, reduced the depression level and improved cognitive functions. Moreover, lamotrigine provided a better level of social rehabilitation, and was more effective than carbamazepine in preventing relapses [101]. With regard to lithium carbonate, an 8-week doubleblind controlled trial on 91 female bulimic outpatients


has shown that lithium is no more effective than placebo in reducing binge episodes and related psychopathology. As a limitation, lithium was administered in a dosage that yielded relatively low plasma levels [65, 66]. If we look at opioid medications, in the literature there is a generic consensus on the ability of opioid antagonists to reduce binge/purge symptomatology and food intake, especially if used in association with fluoxetine. The most widely studied drug is naltrexone, which has proved to significantly reduce the hedonic response to food, ultimately leading to weight loss. With regard to the new opioid agent nalmefene, it has been shown to decrease appetite, average meal size and daily food intake and to increase meal frequency in animals, but its effects on body weight are less clear in chronic administration, if compared with naltrexone. We can speculate that the development of tolerance to some of the effects of nalmefene could be due to its partial agonism on k-opioid receptors. On the other hand, the anti-dysphoric, mood-stabilizing effects of k-partial agonism could be useful too in treating normal weight bulimic patients, because they have reported high rates of bipolar comorbidity, both in the full-blown disorders and at the affective temperamental level. In summary, opioid antagonists have been shown to be effective in reducing bulimic symptomatology and generic food intake, both in humans and animals. Within this class of pharmacological agents, naltrexone and nalmefene seem to present some differences, with the former being more effective on weight gain, and the latter on mood instability. These opioid agents, especially in the case of naltrexone, should be associated with serotoninergic and anticonvulsivant drugs, the former used to counter the dysphoric effects of naltrexone, the latter to achieve mood stabilization. On the other hand, nalmefene should be preferred to naltrexone in bipolar patients of normal weight, who are likely to benefit from a double stabilization.

reuptake inhibitors have been reported to be modestly effective in reducing binge eating over the short term in both illnesses. Among mood stabilizers, topiramate has consistently been shown to decrease binge eating not only in bulimia nervosa but also in binge eating disorder [107, 108]. Another review of double blind, placebo-controlled pharmacological studies has suggested that antidepressant treatment might be associated with a reduction in binge frequency in obese patients with binge eating disorder, without leading to significant weight reduction [154]. The longer-term effects of antidepressant medications, for the treatment of bulimia nervosa and binge eating disorder, have also been reviewed. The use of a single antidepressant agent has resulted in the recovery of about 25% of patients entering treatment; continued treatment was accompanied by relapse in about one-third of patients. The substitution of one or more antidepressants for the initial agent in patients who failed to improve or could not tolerate side-effects led to the improvement of long-term maintenance [4]. With regard to opioid medications, the compounds that have been tested for their use in bulimia have been successfully evaluated in binge eating disorders too, with a few differences that are related to the peculiarities of the two disorders. In binge eating disorder one important issue is body weight, which seems to undergo no substantial repercussions from the antidepressant agents commonly used in these patients. For this reason we suggest that, among opioid medications, the first choice should be naltrexone, especially in obese patients who have no clear bipolar diathesis. Even more than in the case of bulimia, opioid antagonists should be associated with serotoninergic compounds, which, while they have little effect on body weight, have the advantage of counteracting the pro-dysphoric effects of naltrexone. The most important considerations are summarized in table 1. 5.

Conclusions

4.4. Binge eating disorder The presence of clinical and psychological overlapping between binge-eating disorder and bulimia nervosa has prompted researchers to experiment, in the first disorder, the agents that have to be of some efficacy in the second one. Randomized controlled trials on specific medications used to treat patients with bulimia nervosa and binge eating disorder have been reviewed. With regard to antidepressant agents, selective serotonin

Despite the low availability of clinical and epidemiological data on the correlations between eating disorders and opiate addiction, evidence from both human and animal studies prompt the suggestion that opioid medications may play a significant role in the treatment of eating disorders. The most impressive findings so far have been those that refer to the usefulness of opioid antagonists and partial agonists in binge eating disorder and bulimia nervosa, especially when employed in association with standard treat- 27 -


Table 1. Most important considerations regarding the role of the opioid system in Eating Disorders Eating disorders share an alteration in the reward system, a relatively well-defined form of brain circuitry that plays a central role in instinctual drives, such as those involved in sexual, aggressive and feeding behaviours. From a hierarchical point of view the opioid system is situated at the highest level of the reward system. It is responsible for the control of pain, reward, attachment and addictive behaviours. Opioid agents are generally classified as agonists or antagonists according to their intrinsic activity on opioid receptors. Full agonists have maximal efficiency and produce similar effects to those of endogenous opioids. Partial agonists have intermediate efficiency and produce sub-maximal effects, compared with those of endogenous opioids. Antagonists counteract the effects of full and partial agonists, inducing a withdrawal state in people who are tolerant to opiates. There is a low level of availability of data on the correlations between opiate addiction and eating disorders, both on the epidemiological and the clinical plane. The high rate of comorbidity of both disorders with bipolar spectrum conditions is supportive of there being a bipolar connection between the two diseases. Opioid full and partial agonists seem to present a promising profile of effects that could be useful in the treatment of anorexia nervosa. Besides enhancing food intake, they display all the pharmacological properties presented by the most commonly used medications. Methadone is a synthetic full agonist of the mu-opioid receptors. It has a mean elimination half-life of 22 hours, and its actions on feeding behaviours are not subject to tolerance phenomena. Because of poor handling and more side-effects, we speculate that it might be used in anorexic patients that have proved to be resistant to buprenorphine. Buprenorphine works as a partial agonist at the mu-opioid receptors and as an antagonist on delta- and κ-opioid receptors. It has a half-life of 24–60 hours. We speculate that buprenorphine might be useful in anorexic patients who are resistant to standard treatments. Opioid antagonists have been shown to reduce food intake by attenuating taste-related reward. Of these medications, naltrexone is the most effective on body weight, but is burdened by a pro-dysphoric effect, whereas nalmefene is less effective on body weight, but has the advantage of exerting a mood-balancing and anti-dysphoric effect. Naltrexone is an opioid receptor antagonist commonly used as an anti-reward medication. Its two most active metabolites have half-lives of 4 hours and 13 hours, respectively. We propose using naltrexone in obese patients suffering from binge eating disorder, especially in association with serotoninergic and anticonvulsivant drugs. Nalmefene behaves as a moderately potent antagonist on delta-opioid receptors, as a partial agonist on κ-opioid receptors, and as an antagonist on mu-opioid receptors. It has a plasma half-life of almost 11 h. We speculate that nalmefene should be preferred to naltrexone in bulimic patients of normal weight who, because of their bipolar comorbidity, would benefit from a double stabilization. Opioid medications are good candidates for playing a significant role in the treatment of eating disorders. The most impressive findings are those that refer to the usefulness of opioid antagonists and partial agonists in binge eating disorder and bulimia nervosa, especially when employed in association with standard treatments. Further studies are strongly encouraged to assess the possible effectiveness of opioid agonists on anorexia nervosa symptoms.

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Received December 15, 2013 - Accepted February 10, 2014 - 34 -


Comparing emotional clarity, emotion experience, and emotion regulation in male heroin addicts with and without withdrawal syndrome Zhao Xin1,2, Xie Lu1, Fu Li2, Zhou Renlai2, Jin Ge3,Yang Ling1, and Cai Yueyue1 1 School of Psychology, Northwest Normal University, Lanzhou 730070, China 2 Emotion Regulation Research Center, Beijing Normal University, Beijing 100875,China 3 College of Education, Lanzhou City University, Lanzhou 730070, China

Summary Background: Emotional problems play a key role in inducing relapse among those who suffer from substance addiction. Methods: In the present study, we determine differences in emotional clarity and experience, and the regulation of emotion in the two groups selected by us: 28 men with heroin addiction who were not experiencing physical withdrawal symptoms (M = 39.64, SD = 4.12, range: 32–50 years) and 28 men with heroin addiction who were experiencing such symptoms (M = 40.96, SD = 4.47, range: 32-50 years). To measure these variables, we used the Positive and Negative Affect Schedule, the identification subscale of the Toronto Alexithymia Scale, and the Emotion Regulation Questionnaire. Results: Compared with the abstinent group, the non-abstinent group experienced increased negative emotion and made less use of cognitive reappraisal strategies. In addition, the groups did not significantly differ in emotional clarity, positive emotional experience, or frequency in their use of suppression strategies. Conclusions: Our study suggests that, among heroin addicts, abstinence contributes to the release of negative emotions and the use of effective emotion regulation strategies, but that, at the same time, it failed to enhance positive emotional experiences. Key Words: heroin addicts with physical withdrawal symptoms; heroin addicts without physical withdrawal symptoms; abstinence; emotional clarity; emotional experience; emotion regulation

1.

Introduction

Emerging evidence suggests that emotional processes may be involved in the development of addiction, and that emotional alterations may compromise the effectiveness of treatment approaches to substance abuse. Some studies have examined substance abusers’ emotional experiences, especially with reference to natural affective stimuli that are motivationally relevant to the normal population. These results suggest that the experience of emotions may be significantly altered in substance abusers, and that these alterations may play an important role in the course of drug abuse treatment and its results [1]. Even more important is the fact that, according to the Affective Processing Model of Negative Reinforcement, emo-

tional problems could induce drug-seeking behaviour in drug addicts, ultimately leading to relapse [3]. In the context of emotional processes, the most commonly studied domains include emotional clarity, that is, the ability to identify and understand one’s own emotions [4, 5], emotional experiences – a domain which regards the polarity of the affective states experienced by subjects [18] – and the regulation of emotions, which comprises the cognitive strategies that are used to manage emotional experiences [10]. A large number of researchers are currently investigating the emotional problems of drug-dependent individuals [1, 7, 12, 16, 17, 19], dedicating particular attention to heroin-dependent patients [1, 17]. As partly shown by an earlier study, people with heroin addiction share deficits in the way their

Corresponding author: Zhou Renlai, MD; Emotion Regulation Research Center, Beijing Normal University, Beijing 100875,China E-mail: [email protected]

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emotions are processed, which explains why they are weaker than non-addicted individuals in experiencing emotional stimuli [1]. Few studies, however, have explored the influence of physical withdrawal on the emotional experiences and the control over emotions of heroin-dependent individuals. In order to fill this gap, we compared the emotional states of heroinaddicted individuals with and without physical withdrawal symptoms, focusing on emotional clarity and experience, and emotion regulation. We expected no significant differences in emotional clarity between the two groups. Heroin-addicted individuals with physical withdrawal symptoms were hypothesized to experience more negative emotions, and to possess a lower level of cognitive resources, when compared with heroin-addicted individuals who are free of such symptoms. 2.

Methods

2.1. Sample All 56 male participants were heroin addicts coming from a drug rehabilitation centre in Gansu Province, China. They were divided into two groups: 28 patients who reported they had experienced physical withdrawal symptoms and 28 patients who did not report having experienced such symptoms. According to the DSM-IV diagnostic criteria for opioid dependence, all participants had heroin dependence without psychotic disorder or severe somatic disease. Participants in the abstinent group were in a labour camp and had negative results on a urine test for morphine. Those in the non-abstinent group were undergoing heroin withdrawal. Age did not significantly differ between the abstinent group (M = 40.96, SD = 4.47, range = 32-50 years) and the non-abstinent group (M = 39.64, SD = 4.12, range = 32-50 years), F(1,55) = 1.324, p=ns. 2.2. Instruments 2.2.1 Opiate Withdrawal

Opiate withdrawal symptoms in the two groups were measured by means of the Opiate Withdrawal Scale (OWS) [6]. This scale was developed by Bradley et al. in 1987 to assess the severity of opiate withdrawal symptomatology; it contains 32 items that represent various different symptoms. Each symptom is graded according to severity as follows: 0 = absent, 1= mild, with no need for treatment, 2 = moderate and requiring treatment, and 3 = severe and requiring - 36 -

treatment [6]. 2.2.2 Emotional Clarity

Emotional clarity was measured by applying the Identification Subscale from the Toronto Alexithymia Scale (TAS) [2], which is frequently used to measure individual differences in the ability to identify one’s emotional states. The Identification Subscale comprises seven items. Participants respond on a 5-point Likert scale (1 = “strongly disagree”; 5 = “strongly agree”). Scale scores are computed by calculating the mean of all scale items and scored in such a way that lower scores represent higher levels of emotional clarity [4, 5]. Its reliability was good in the present sample (Cronbach’s alpha = .89) 2.2.3 Emotional Experience

Emotional experience was assessed with the Positive and Negative Affect Schedule (PANAS), a 20-item self-report capable of measuring positive and negative affect. Positive affect (PA) reflects the level of positive affective states experienced by a given person. Negative affect (NA) reflects the degree to which a person feels negative affective states. Responses are assessed on a scale ranging from 1 (very slightly or not at all) to 5 (very much) [18]. Cronbach’s alpha was satisfactorily high for the PA (.87) and NA (.80) schedules. 2.2.4 Regulation of the Emotions

The Emotion Regulation Questionnaire (ERQ) was employed to assess the use of emotion regulation strategies. It measures the frequency of use of two types of strategies: reappraisal (6 items) and suppression (4 items). Cognitive reappraisal is an effective strategy for regulating emotions; it serves to reduce an individual’s negative emotion experiences. Cognitive suppression is the process of deliberately trying to stop thinking certain thoughts. Participants respond to items using a 7-point Likert scale (1 = “strongly disagree”; 7 = “strongly agree”). Cronbach’s alpha was satisfactory for reappraisal (.75). It was only .53 for suppression frequency; the results related to suppression frequency should therefore be interpreted with caution [10]. 2.3. Data analysis Data were examined using one-way analyses of variance. The p values were Bonferroni-adjusted.

Z. Xin et al.: Comparing emotional clarity, emotion experience, and emotion regulation in male heroin addicts with and without withdrawal syndrome

3.

Results

those of the abstinent group (M = 2.52, SD = 0.65), F(1,55) = 4.41, p < .05, χ2 =.08.

3.1 Socio-demographic Data 3.5 Regulation of the Emotions Regarding educational level, in the abstinent group 3 individuals graduated from primary school (10.71%), 14 from middle school (50.00%), 10 from high school (35.71%), and 1 from university (3.57%). In the non-abstinent group, 10 graduated from primary school (37.04%), 13 from middle school (48.15%), 4 from high school (14.81%), and 1 individual failed to provide any information on education (3.57%). The two groups did not show significant differences in educational level, χ2(3) = 7.362, p=ns. In terms of ethnicity, 27 participants (96%) in the abstinent group were of Han ethnicity, and 1 (4%) was of Hui ethnicity; in the non-abstinent group, 24 (86%) were of Han ethnicity, and 4 (14%) of Hui ethnicity. As to marital status, in the abstinent group 7 (25%) were unmarried, 1 (3.6%) was cohabiting but unmarried, 13 (46.40%) were married, and 7 (25%) had divorced. In the non-abstinent group, 2 (7.1%) were unmarried, 1 (3.6%) was cohabiting but unmarried, 12 (42.9%) were married, 8 (28.6%) had divorced, and 5 (17.9%) did not report their marital status. 3.2 Opiate Withdrawal As expected, the scores of the non-abstinent group (M = 48.96, SD = 17.95) on the Opiate Withdrawal Scale were significantly higher than those of the abstinent group (M = 38.07, SD = 14.41), F(1,55) = 6.271, p < .05, χ2 = 0.104. The scale showed good reliability in the present sample (Cronbach’s alpha = .96). 3.3 Emotional Clarity There was no significant difference in emotional clarity between the abstinent group (M = 3.13, SD = 0.54) and the non-abstinent group (M = 2.89, SD=0.67), F(1,55) = .309, ns. 3.4 Emotional Experience As shown in figure 1, there was no significant difference in positive emotional experience between the abstinent group (M = 2.26, SD = 0.64) and the non-abstinent group (M = 2.20, SD = 0.72), F(1,55) = .124, ns. However, in the assessment of negative emotional experience, scores of the non-abstinent group (M = 2.89, SD = 0.67) were significantly higher than

As shown in figure 2, the use of suppression did not differ significantly between the abstinent group (M = 4.31, SD = 0.66) and non-abstinent group (M = 4.33, SD = 0.88), F(1,55) = .007, p=ns. However, cognitive reappraisal was used more frequently in the abstinent group (M = 4.67, SD = 0.72) than the non-abstinent group (M = 4.18, SD = 0.76), F(1,55) = 6.095, p < .05, χ2 = .10. 4.

Discussion

We compared the emotional clarity and experience, and the emotion regulation of heroin-addicted individuals with and without physical withdrawal symptoms. With regard to emotional clarity, our study demonstrated that there was no prominent difference between the two groups. Emotional clarity is the ability to identify and understand one’s emotional experiences, and is related to emotional intelligence and emotion regulation [4, 5]. It is plausible that emotional intelligence acts as a stable individual quality that is not affected by the presence of withdrawal symptoms. The absence of between-group differences in emotional clarity indicates that it cannot account for the differences in emotional experience and the regulation of emotion between the two groups. With regard to emotional experience, our results offer substantial evidence that heroin-addicted individuals with physical withdrawal symptoms experience stronger negative emotion than those without such symptoms, in line with our hypothesis. We propose that the lower level of negative emotional experience in the abstinent group was mainly caused by the gradual reduction in physical symptoms. Further evidence in favor of this proposal comes from the significant correlation between scores on the Opiate Withdrawal Scale (OWS) and those on the negative affect subscale of the PANAS, r = 0.41, p = 0.002. Positive emotional experience did not noticeably differ between the two groups. Although no physical symptoms were recorded in individuals who experienced physical withdrawal, they still appear to need social attention and support to experience more positive emotions. Moving on now to the regulation of the emotions, we found that heroin-addicted individuals - 37 -


Figure 1. Scores on the Positive and Negative Affect Schedule of the group with physical withdrawal (PW) and the group without physical withdrawal (NPW) (PW: physical withdrawal symptomatology, NPW: non-physical-withdrawal symptomatology)

Figure 2, Scores on the Emotion Regulation Questionnaire (frequency of using two types of emotion regulation: reappraisal and suppression) of the two groups (PW: physical-withdrawal symptomatology, NPW: non physical-withdrawal symptomatology)

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Z. Xin et al.: Comparing emotional clarity, emotion experience, and emotion regulation in male heroin addicts with and without withdrawal syndrome

without physical withdrawal symptoms use cognitive appraisal to a greater extent than those with physical withdrawal, which is consistent with our hypothesis. Cognitive appraisal is an antecedent-focused strategy employed in the early stages of emotion [11]; it changes an individual’s understanding of emotional events in a way that reduces emotional reactivity [10, 11, 15]. We suggest that, compared with the physical-withdrawal participants, who are affected by physical symptoms, participants in the abstinent group were more prone to experiencing severe anxiety and depression. Under the influence of such emotions, individuals would focus more on their obsessive thoughts, concerns, and negative cognitions, which could occupy and consume limited cognitive resources, ultimately leading to the use of appraisal [8, 9, 14]. Although we also found a slight difference in the use of suppression, the low reliability of the suppression scale indicates that this result should be interpreted with caution. Limitations There are several limitations that affect our study. First, the small sample limits the extent to which our findings can be generalized. To extend the validity of our results, future studies should use a larger sample. Second, future studies could use a longitudinal design with follow-ups instead of a between-group design to identify long-term changes in emotional experience, regulation and clarity by assessing the same group of participants before and after they experience physical withdrawal. Lastly, all the participants in our study were male, while it should be borne in mind that previous researchers found gender differences in emotional experience and regulation [13]. This raises a number of questions about the differences in emotional experience and the regulation of emotions between heroin-addicted women who have experienced physical withdrawal and those who have not. 5.

Conclusions

This study emphasizes the influence of heroin withdrawal on the individual’s emotional experience. Heroin-addicted individuals without physical withdrawal symptoms tend to experience more negative emotions, and to make less use of cognitive resources, than heroin-addicted individuals with such symptoms.

References 1. Aguilar De Arcos F., Verdejo-Garcia A., Peralta-Ramirez M. I., Sanchez-Barrera M., Perez-Garcia M. (2005): Experience of emotions in substance abusers exposed to images containing neutral, positive, and negative affective stimuli. Drug Alcohol Depend. 78(2): 159-167. 2. Bagby R. M., Taylor G. J., Parker J. D. (1994): The Twenty-item Toronto Alexithymia Scale--II. Convergent, discriminant, and concurrent validity. J Psychosom Res. 38(1): 33-40. 3. Baker T. B., Piper M. E., Mccarthy D. E., Majeskie M. R., Fiore M. C. (2004): Addiction motivation reformulated: an affective processing model of negative reinforcement. Psychol Rev. 111(1): 33-51. 4. Boden M. T., Bonn-Miller M. O., Kashdan T. B., Alvarez J., Gross J. J. (2012): The interactive effects of emotional clarity and cognitive reappraisal in Posttraumatic Stress Disorder. J Anxiety Disord. 26(1): 233-238. 5. Boden M. T., Gross J. J., Babson K. A., Bonn-Miller M. O. (2013): The interactive effects of emotional clarity and cognitive reappraisal on problematic cannabis use among medical cannabis users. Addict Behav. 38(3): 1663-1668. 6. Bradley B. P., Gossop M., Phillips G. T., Legarda J. J. (1987): The development of an opiate withdrawal scale (OWS). Br J Addict. 82(10): 1139-1142. 7. Cheetham A., Allen N. B.,Yucel M., Lubman D. I. (2010): The role of affective dysregulation in drug addiction. Clin Psychol Rev. 30(6): 621-634. 8. Derakshan N., Eysenck M. (2009): Anxiety, Processing Efficiency, and Cognitive Performance. New Developments from Attentional Control Theory. European Psychologist. 14(2): 168-176. 9. Elliman N., Green M., Rogers P., Finch G. (1997): Processing-efficiency theory and the working-memory system: Impairments associated with sub-clinical anxiety. Personality and Individual Differences. 23(1): 31-35. 10. Gross J. J., John O. P. (2003): Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J Pers Soc Psychol. 85(2): 348-362. 11. John O. P., Gross J. J. (2007): Individual differences in emotion regulation strategies: Links to global trait, dynamic, and social cognitive constructs. In: Press G. (Ed.) Handbook of emotion regulation. New York. pp. 351-372. 12. Magyar M. S., Edens J. F., Lilienfeld S. O., Douglas K. S., Poythress N. G. (2011): Examining the relationship among substance abuse, negative emotionality and impulsivity across subtypes of antisocial and psychopathic substance abusers Journal of Criminal Justice. 39: 232-237. 13. Mcrae K., Ochsner K. N., Mauss I. B., Gabrieli J. J. D., Gross J. J. (2008): Gender differences in Emotion Regulation: An fMRI Study of Cognitive Reappraisal.

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Group Processes Intergroup Relations. 11(2): 143-162. 14. Miller H., Bichsel J. (2004): Anxiety, working memory, gender and math performance. Personality and Individual Differences. 37(3): 591-606. 15. Samson A. C., Huber O., Gross J. J. (2012): Emotion regulation in Asperger’s syndrome and high-functioning autism. Emotion. 12(4): 659-665. 16. Verdejo-Garcia A., Bechara A., Recknor E. C., PerezGarcia M. (2007): Negative emotion-driven impulsivity predicts substance dependence problems. Drug Alcohol Depend. 91(2-3): 213-219. 17. Wang Z. X., Zhang J. X., Wu Q. L., Liu N., Hu X. P., Chan R. C., Xiao Z. W. (2010): Alterations in the processing of non-drug-related affective stimuli in abstinent heroin addicts. Neuroimage. 49(1): 971-976. 18. Watson D., Clark L. A., Tellegen A. (1988): Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 54(6): 1063-1070. 19. Zhang M., Zhu H., Li X., Shui R., Shen M. (2012): Biased number perception of schematic expressions in abstinent heroin abusers compared to normal controls. J Behav Ther Exp Psychiatry. 43(1): 602-606.

Role of the funding source This work was supported by The National Natural Science Foundation of China (31300838, 31360233), The Young Teacher Research Capacity Advancement Program of Northwest Normal University (SKQNYB12009) and Open Research Fund of the Beijing Key Lab of Applied. Contributors Zhao Xin, Zhou Renlai and Jin Ge designed research; Zhao Xin, Jin Ge, Cai Yueyue and Yang Ling analyzed data; Zhao Xin and Fu Li wrote the paper. All authors contributed to and have approved the final manuscript. Conflict of interest All authors declare that they have no conflicts of interest.

Received November 3, 2013 - Accepted January 26, 2014 - 40 -


Why do heroin users refuse to participate in a heroin-assisted treatment trial? Isabelle Demaret 2, Géraldine Litran 2, Cécile Magoga 2, Clémence Deblire 2, Anicée Dupont 2, Jérôme De Roubaix 1,2, André Lemaître 1, and Marc Ansseau 2 1. Institute for Human and Social Sciences (Criminology), University of Liège, Belgium, EU 2. Department of Psychiatry, University of Liège, Belgium, EU

Summary Background: Heroin-assisted treatment (HAT) can improve the condition of heroin addicts who are resistant to other treatments. However, in a new HAT trial in Belgium, fewer subjects than expected were included. Aim: Our research team explored the reasons given by heroin users in explaining why they did not want to participate. Methods: In 2011, during the trial recruitment, we interviewed heroin users (n=52) who never took the opportunity to meet the research team during the recruitment process preceding the trial. Results: Of those 52 heroin users, 25 were afraid of the limited length of the HAT and 11 feared becoming more dependent as a result of HAT. Conclusion: A trial that was planned to last for a limited length of time may have demotivated heroin users who could otherwise have benefited from this new programme. Key Words: Heroin; treatment; motivation; addiction

1.

Introduction

Methadone is the most strongly recommended treatment for heroin addiction [1, 12]. However, a considerable percentage of severely affected heroin addicts still use street heroin frequently, in spite of being in a methadone treatment. These heroin addicts who are considered to be treatment-resistant display numerous physical and mental health problems, social difficulties and criminal involvement [19]. Heroin-assisted treatment (HAT) is one of the options available for improving the condition of these treatment-resistant heroin addicts. In this second-line programme, a physician prescribes diacetylmorphine (DAM) to severely affected heroin addicts. Patients administer DAM themselves under the supervision of

nurses, in a specific centre, as frequently as twice or three times a day. Since 1994, six randomized controlled trials have been conducted using this supervised treatment model: in Switzerland [17], in the Netherlands [19], in Spain [10], in Germany [7], in Canada [15] and in the United Kingdom [18]. In each trial, the research team concluded that HAT showed greater efficacy in the treatment of severely affected heroin addicts than oral methadone maintenance. A Cochrane review [5] confirmed that HAT could improve the condition of this special target group: treatment-resistant, severely addicted heroin users. However, in each of these trials, fewer subjects than expected were included, and each trial reported between 14% and 45% of heroin users who went no

Corresponding author: Isabelle Demaret, Institute for Human and Social Sciences, Boulevard du Rectorat 3 (B31), 4000 Liège, BELGIUM, EU Telephone: 00.32.4.366.31.58; Fax: 00.32.4.366.98.08; E-mail:[email protected]

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further in the inclusion process after at least one contact [2, 6, 9, 10, 14, 15, 17, 18]. The trial reports did not include any information to explain why these users left the process. The same phenomenon happened in Belgium, during the recruitment process preceding a HAT trial. Methadone centres, which had the responsibility of referring participants to the trial, informed the research team that some heroin addicts did not seem interested in the trial, despite their continuous use of street heroin while in methadone treatment. With the aim of exploring their attitude towards the trial, we interviewed heroin addicts who had never taken the opportunity to attend a meeting with the research team. We encountered them in specialized addiction centres and in the street. We hope that this study will help health care workers and policy makers to understand why HAT programmes are not as attractive as had originally been expected to severely ill heroin addicts. 2.

Methods

2.1. Trial TADAM (Treatment Assisted by Diacetylmorphine) is an open label, randomized, controlled trial, which began in Liège (Belgium) in January 2011 and ended in January 2013. Results will not be published before 2014. The expectation was for 200 subjects to be recruited in 12 months, a hundred subjects for each of the two groups. The experimental group received a HAT for 12 months in a new setting, and the control group received methadone maintenance treatment in existing addiction centres (official partners of the trial). Subjects had to come to the new HAT centre up to three times a day. They could choose to inject or inhale diacetylmorphine, as in the Dutch trial [2, 4, 19]. After 12 months, HAT was definitively stopped, and the best alternative treatment available was offered to the participants. This limited time for the diacetylmorphine programme was decided by the Federal government for legal and political reasons. The Ethics Committee of the Faculty of Medicine (University of Liège) approved this trial in 2010. The TADAM centre, located in the middle of the city of Liège, was easily accessible by foot or public transport. In order to forestall potential opposition from neighbours, the City installed the centre next to a police station.

2.2. Inclusion criteria The inclusion criteria were intended to recruit subjects with severe heroin addiction that had resisted previous treatment. This was demonstrated by a heroin dependency of at least 5 years, a daily or almost daily use of illicit heroin, and at least one previous experience of methadone treatment (with a minimum daily dose of 60 mg). We considered that these criteria showed a heroin addiction that resisted other treatments, even if we did not have data detailed enough to allow us to assess whether the previous methadone treatment was adequate or not. However, other HAT trials [7, 15, 18] showed that, even with an optimized and controlled methadone treatment, HAT was more effective than methadone for participants who met our inclusion criteria. Another requirement was for participants to have been legal residents of the judicial district of Liège for at least 12 months. Each participant signed an informed consent form. The only official documents necessary for the first meeting with researchers were a legal identification document and a legal document with a history of domicile, directly available from the municipal offices. 2.3. Partner centres The TADAM trial worked with nine partner centres that were responsible for the first step of the recruitment process. Each heroin user interested in the project had to be registered in one of these centres before coming to the research team for evaluation. Heroin users were free to choose a centre, and partner centres were free to refer or not to refer a heroin user to the research team. 2.4. Inclusion process The partner centres referred 116 heroin users who wanted to participate in the trial. Thirty-three users (28%) did not show up to meet the research team. Nine potential participants (8%) were excluded from the trial because they did not meet the inclusion criteria. As shown by their baseline characteristics, the HUI (Table 1) were severe heroin users (they had used street heroin for an average of 20 years) who were resistant to existing treatments (they had experienced an average of nine previous treatments). 2.5. Opinions of heroin users who were not included In order to understand the opinions of other

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I. Demaret et al.: Why do heroin users refuse to participate in a heroin-assisted treatment trial?

Table 1: Baseline characteristics of the heroin users included (HUI) Sociodemographic characteristicsa

n = 74 43 [7] 65 (88%) 2 (3%) 21 (28%) 69 (93%) 56 (76%) 37 (50%) 20 [7] 27 [5] 14 [7] 21 (28%) 34 (46%) 31 (42%) 60 (81%) 21 (28%) 9 [13]

Age – years Male sex Employed (last month) No stable housing last month Ever convicted Ever incarcerated Illegal activities last month Drug use Regular heroin use – years Heroin last month – days Regular methadone use – years Alcohol last month (+ 5 glasses per day) Cocaine last month Benzodiazepines last month Ever injected Injection past month Number of previous drug treatments a

Data are number of heroin users (%) or mean [s.d.]

heroin users about the trial, we interviewed users who had not met the research team during the recruitment process. To simplify the issue, they are called "HUNI“, an acronym standing for "heroin users not included in the study". Our inclusion criteria for this group were a current or recent history of street heroin use, and the fact of having failed to meet the research team during the recruitment process for the TADAM trial. We encountered them on the street, in places known for drug dealing (helped by a social worker familiar with heroin users in the city), in two specialized addiction centres (partners in the project) and in one harm reduction service for drug users (managed by another partner centre). The three services were considered low threshold, as they accepted all active heroin or cocaine users without requiring the user to stop or reduce drug use. In order to collect the spontaneous answers of heroin users, we arranged no appointments; the subjects were interviewed directly by us when first encountered. After posing questions about sociodemographic and substance abuse characteristics, the researcher asked if the user was aware of the TADAM trial, how he (or she) knew about it, if he/she was interested in participating and why. With the approval of the subject, we tape-recorded each interview. The interviews were transcribed verbatim with the protection of anonymity. We used NVivo 9 to analyse and sort the opinions expressed in the interviews.

2.6. Sample description: users not included The research team interviewed 52 HUNI between July 11, 2011 and January 17, 2012. Two researchers interviewed the same heroin user, and their separate interviews were then merged. The 52 HUNI had never been assessed by the research team for the TADAM trial and, therefore, had not been excluded from the trial recruitment process. 22 interviewees had taken part in a meeting in addiction centres, 18 in a low threshold service and 12 on the street. 48 of the HUNI (92%) were male. The mean age was 40 years; and 30 (58%) had an unstable housing situation (Table 2). According to our interviews, 35% would not have met the (almost) daily heroin use criterion set for the trial. 3.

Results

3.1. Knowledge of the trial One HUNI had not heard about the project. The others (n=51) knew of it through the addiction field (n=34), or through other heroin users (n=24), other unspecified informants (n=17), the media (n=9) or the police (n=2). The main source of information, the addiction field, included social workers, physicians and street workers, but also folders and posters distributed by the research team.

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Table 2: Characteristics of the heroin users not includeda (HUNI) n=52 Sociodemographic characteristics - Male - Mean age - No stable housing

48 (92%) 40 [7]* 30 (58%) Drug use

- Age at first heroin use - years - Started heroin use at least 5 years ago Current heroin use - 2 times or more per week - 1 time per week or less - no heroin use - no information Usual route of administration - by inhalation - by injection - no preference - no information

19 [4]** 52 (100%) 25 (48%) 12 (23%) 6 (12%) 9 (17%) 33 (63%) 7 (13%) 3 (6%) 9 (17%)

Data given refer to the number of heroin users (%) or a mean value [s.d.] * n=51 ** n=50 a

3.2. Desire to participate in the HAT trial Of the 51 HUNI who were aware of the project, 40 were not interested in participating, 7 were interested, 3 did not answer clearly and 1 refused to answer. Of the 48 who explained their attitude towards the project, 47 gave one or more reasons for their decision against participation, and 18 gave one or more reasons for participating. 17 users gave reasons both pro and con. 3.3. Why heroin users did not want to enter the TADAM trial A majority of HUNI (n=31) did not want to enrol in the project because of the trial conditions (Table 3), particularly the limit of the duration of HAT to one year (n=25). 28 HUNI did not want to enter a HAT because of the diacetylmorphine itself, mainly because they wanted to decrease their street heroin use (n=14) or because they were afraid of exacerbating their addiction by having a perpetually available supply of pure heroin (n=11). For 16 HUNI, HAT conditions (not linked to the trial) explained their refusal to participate in the project. Their answers demonstrated that some of them had been accurately informed about the specificity of HAT (Table 3). For 5 HUNI, the proximity of the police station was a reason for not participating. 3 HUNI were not against participation, but wanted more information about the project.

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Another HUNI explained that he could not begin a treatment because of his jail sentence. Of the 40 HUNI who refused to participate, 18 were frequent heroin users (at least a few times a week) and 17 of those frequent heroin users cited a trial condition as a reason for not participating (data not included in tables). 4.

Discussion

In the course of this study, we analysed the reasons given by heroin users for not participating in the TADAM trial. 40 HUNI refused to enter the project. Of these, 18 were frequent heroin users (belonging to the target group of TADAM). The trial conditions were the main reasons given for having refused to enter the trial. More than half of the HUNI did not want to participate because they were afraid for their future: 25 were afraid to resume their street heroin use after the 12-month treatment, 11 feared becoming more addicted, and 30 gave one or both arguments. These heroin users were conscious of their addiction and afraid of aggravating it. Refusal of the project by many potential participants because of the limited length of HAT can be seen as a sign of their insight into their severe addiction: as they explained in many cases, they were afraid of returning to their street heroin use if DAM was scheduled to be stopped after 12 months. Moreover, 23 of the 25 HUNI who were afraid of the limited


Table 3: Reasons for not participating Users (%) n=51 47 (92%) 31 (61%) 25 (49%) 7 (14%) 7 (14%) 2 (4%) 28 (55%) 14 (27%) 11 (22%) 8 (16%) 1 (2%) 16 (31%) 5 (10%) 5 (10%) 4 (8%) 3 (6%) 2 (4%) 2 (4%) 1 (2%) 1 (2%)

At least one reason against participating Reasons linked to the trial conditions - heroin-assisted treatment limited to 12 months - randomizing - problems with other trial conditions (formalities or inclusion criteria) - being used as a guinea-pig Reasons linked to diacetylmorphine - want to decrease or stop heroin use - afraid to become more addicted - prefer methadone or buprenorphine - do not like diacetylmorphine Reason linked to diacetylmorphine treatment conditions - diacetylmorphine centre is next to a police station - being with drug addicts - going every day - being able to use diacetylmorphine only in the centre - no smoking of cigarettes while inhaling - not enough time to smoke heroin - too much control - using heroin in front of other people Other reasons - need more information - will soon be in prison

length of HAT had been addicted for 10 years or more, and 19 had experienced a methadone treatment. This is consistent with the observation that insight into the illness is high in heroin addicts who have a long history of severe heroin addiction [11]. It should be added that, even with an open-ended duration of treatment, HAT would not attract every severely ill heroin addict. As shown by our interviews, some heroin users seemed to have been repelled by the process of undergoing HAT and probably by the hetero-administrative aspects of this programme: consuming in front of others, being controlled, no take-away, going every day. Refusal of the trial for

3 (6%) 1 (2%)

these reasons could be seen as a refusal to enter a HAT programme and as a serious outcome that was due to heroin addiction. The six other trials had been planned to include a higher number of heroin users than the number actually participating (Table 4), even though the recruitment period lasted more than 12 months in The Netherlands [19], in Germany [7], in Canada [16] and in the United Kingdom [18]. Between 14% and 45% of the heroin users who had at least one contact with a trial team refused to continue or did not return. In publishing their results, the authors of the studies did not explain why heroin users had stepped

Table 4: Trials recruited between 26% and 91% of the expected number of participants CH Subjects initially planned Heroin users with at least one contact with the recruitment team Heroin users included Ratio included/planned Ratio included/with at least one contact

80

NL 625

73 51 64% 70%

SP 240

GE 1120

CA 470

UK 150

BE 200

1500

176

2083

581

301

116

549 88% 37%

62 26% 35%

1015 91% 49%

251 53% 43%

127 85% 42%

74 37% 64%

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back from the recruitment process. One study showed that willingness to participate in a HAT trial was associated with daily heroin use and current methadone treatment, but failed to explain why 38% of the users contacted refused to participate in a HAT programme [13]. Limitations 52 heroin users is too low a number to adequately represent the hundreds of heroin users in the city [3]; neither were they representative of the trial target group, as 18 (35%) were not frequent street heroin users. However, 52 interviews should make up a sufficently large sample to collect the main reasons given by heroin users for or against entering our trial. We recorded the interviews as a way to document each reason that was given. So, even if our 52 users did not represent the target group of the trial, the arguments collected in our 52 interviews could still reflect the main lines of argument circulating in this group. We must remember that the reasons that were expressed for and against acceptance were given by severely affected heroin addicts for whom (by definition) heroin use was a central motivation. 5.

Conclusions

The HUNI were severely affected heroin addicts and their reasons for refusing to participate were not uniform. The explanation for the lack of interest of heroin users was related to their attitude towards the trial, HAT conditions or DAM itself. But the main reason given was the limited length of HAT duration. Heroin users were far more circumspect about a HAT trial than expected. Their concern about the limited duration of HAT and the related fear of resuming heroin use after 12 months can attest a high degree of insight into their illness. Fixing an arbitrary time limit for HAT, even in the framework of a pilot project, may have contributed to discouraging severe ill heroin addicts from participating in a programme that has demonstrated its efficacy [5] for this chronic relapsing disease [8]. A year of recruitment may also have been too short a time for people to take the time they needed to observe the new programme and its outcome, to discuss it with medical or social workers, think about it and only then make up their minds. Even if there would still have been a group of severely affected heroin users who refused to enter in this programme, HAT without a predetermined duration would have attract- 46 -

ed more heroin users especially those possessing a high level of insight into their illness. References 1. Amato L., Davoli M., Perucci C. A., Ferri M., Faggiano F., Mattick R. P. (2005): An overview of systematic reviews of the effectiveness of opiate maintenance therapies: available evidence to inform clinical practice and research. J Subst Abuse Treat. 28(4): 321-329. 2. Central Committee on the Treatment of Heroin Addicts (2002). Medical co-prescription of heroin: Two randomized controlled trials: Utrecht, the Netherlands. p 180 3. Demaret I., Herné P., Lemaître A., Ansseau M. (2011): Feasibility assessment of heroin-assisted treatment in Liège, Belgium. Acta Psychiatrica Belgica. 111(1): 3-8. 4. Demaret I., Lemaitre A., Ansseau M. (2012): Staff concerns in heroin-assisted treatment centres. J Psychiatr Ment Health Nurs. 19(6): 563-567. 5. Ferri M., Davoli M., Perucci C. A. (2011): Heroin maintenance for chronic heroin-dependent individuals. Cochrane Database Syst Rev(12): CD003410. 6. Gartry C. C., Oviedo-Joekes E., Laliberte N., Schechter M. T. (2009): NAOMI: The trials and tribulations of implementing a heroin assisted treatment study in North America. Harm Reduct J. 6: 2. 7. Haasen C., Verthein U., Degkwitz P., Berger J., Krausz M., Naber D. (2007): Heroin-assisted treatment for opioid dependence: randomised controlled trial. Br J Psychiatry. 191: 55-62. 8. Leshner A. I. (1997): Addiction is a brain disease, and it matters. Science. 278(5335): 45-47. 9. Lintzeris N., Strang J., Metrebian N., Byford S., Hallam C., Lee S., Zador D. (2006): Methodology for the Randomised Injecting Opioid Treatment Trial (RIOTT): evaluating injectable methadone and injectable heroin treatment versus optimised oral methadone treatment in the UK. Harm Reduct J. 3: 28. 10. March J. C., Oviedo-Joekes E., Perea-Milla E., Carrasco F. (2006): Controlled trial of prescribed heroin in the treatment of opioid addiction. J Subst Abuse Treat. 31(2): 203-211. 11. Maremmani A. G. I., Rovai L., Rugani F., Pacini M., Lamanna F., Bacciardi S., Perugi G., Deltito J., Dell’osso L., Maremmani I. (2012): Correlations between awareness of illness (insight) and history of addiction in heroin-addicted patients. Front Psychiatry. 3. 12. Mattick R. P., Kimber J., Breen C., Davoli M. (2008): Buprenorphine maintenance versus placebo or methadone maintenance for opioid dependence. Cochrane Database Syst Rev (2): CD002207. 13. Miller C. L., Strathdee S. A., Kerr T., Small W., Li K., Wood E. (2005): Factors associated with willingness to participate in a heroin prescription program among injection drug users. J Opioid Manag. 1(4): 201-203. 14. Naber D., Haasen C. (2006). The German model project


for heroin assisted treatment of opioid dependend patients: A multi-centre, randomised, controlled treatment study.: Hambourg, Germany. p 167 15. Oviedo-Joekes E., Brissette S., Marsh D. C., Lauzon P., Guh D., Anis A., Schechter M. T. (2009): Diacetylmorphine versus methadone for the treatment of opioid addiction. N Engl J Med. 361(8): 777-786. 16. Oviedo-Joekes E., Nosyk B., Brissette S., Chettiar J., Schneeberger P., Marsh D. C., Krausz M., Anis A., Schechter M. T. (2008): The North American Opiate Medication Initiative (NAOMI): profile of participants in North America’s first trial of heroin-assisted treatment. J Urban Health. 85(6): 812-825. 17. Perneger T. V., Giner F., Del Rio M., Mino A. (1998): Randomised trial of heroin maintenance programme for addicts who fail in conventional drug treatments. BMJ. 317(7150): 13-18. 18. Strang J., Metrebian N., Lintzeris N., Potts L., Carnwath T., Mayet S., Williams H., Zador D., Evers R., Groshkova T., Charles V., Martin A., Forzisi L. (2010): Supervised injectable heroin or injectable methadone versus optimised oral methadone as treatment for chronic heroin addicts in England after persistent failure in orthodox treatment (RIOTT): a randomised trial. Lancet. 375(9729): 1885-1895. 19. Van Den Brink W., Hendriks V. M., Blanken P., Koeter M. W., Van Zwieten B. J., Van Ree J. M. (2003): Medical prescription of heroin to treatment resistant

heroin addicts: two randomised controlled trials. BMJ. 327(7410): 310. Acknowledgement We thank the heroin users and staffs who kindly received us in their addiction centres where we were able to interview their patients. We also thank the Drug Cell of the Federal Public Service of Health, Food Chain Safety and Environment who was in charge of the administrative follow up of the TADAM assessment. Role of the funding source Besides authors' contribution, the funding sources (Federal Minister of Social Affairs and Public Health, the University of Liège and the City of Liege) were not involved in the collection, analysis and interpretation of data and in the writing of the report. Contributors Isabelle Demaret, Géraldine Litran, Cécile Magoga, Clémence Deblire, Anicée Dupont and Jérôme De Roubaix contributed to the collection and analysis of the data. Isabelle Demaret, André Lemaître and Marc Ansseau contributed to the interpretation of the data and redaction of this manuscript. Conflict of interest The authors report no conflicts of interest. This study and the writing of this paper were funded by the Federal Minister of Social Affairs and Public Health, by the University of Liège and the City of Liege.

Received October 19, 2013 - Accepted February 15, 2014 - 47 -


Sexual dysfunction in male patients receiving methadone and buprenorphine maintenance treatment in Iran Shadan Tafreshian, Meisam Javadi, Fariba Fakhraei, and Seyedeh Seddigheh Fatemi Methadone Clinic, Mashhad University of Medical Sciences, Mashhad, Iran

Summary Background: methadone and buprenorphine are the major modalities of substitution treatment for opioid dependence in Iran. There are still only limited data on alterations in sexual function during methadone or buprenorphine maintenance therapy (MMT, BMT) and the impact of sexual dysfunctions on patients' life and treatment. Aims: to evaluate whether the incidence of sexual dysfunctions differs in samples of men in maintenance treatment with methadone or those with buprenorphine; evaluate correlations between sexual dysfunction and substitution treatment of opioid dependence. Methods: 158 opioid-dependent men were recruited from two methadone maintenance clinics in Mashad, Iran, between December 2011 and April 2013. Data were collected by organizing interviews and questionnaires. Sexual function has been investigated with IIEF, an extensively validated questionnaire covering five domains of male sexual function. Results: methadone has stronger effects on sexual dysfunction than buprenorphine. In both groups, erectile dysfunction seems to be the main form of sexual dysfunction. Methadone dose and the duration of therapy showed a correlation with sexual dysfunction: (p=0.011) and (p=0.012), respectively. On the other hand, no valuable statistical correlations were found between duration of opioid use and sexual complaints in our patients. Conclusions: the frequency of sexual dysfunction in people treated with methadone is higher than in the BMT group. Sexual dysfunctions lowered the quality of patients’ sexual life and damaged their most intimate relationships. This problem may increase the risk of treatment failure and illicit drug abuse. Thus, physicians should screen sexual dysfunctions in men receiving opioid treatment and carefully assess the issue of the medication of choice. Erectile and orgasmic dysfunctions may respond to methadone dose reduction. Further studies are needed to evaluate the benefits of methadone dose reduction in patients receiving treatment. Key Words: Methadone; Buprenorphine; Methadone Maintenance Therapy (MMT); Buprenorphine Maintenance Therapy (BMT); Sexual Dysfunction; Erectile Dysfunction

1.

Introduction

In Iran, as in many other countries, methadone and buprenorphine are currently the most commonly used, most effective medications for the treatment of opioid dependence. A number of publications describe hypoactive sexual desire, erectile and orgasmic dysfunction with opioid use [9]. Sexual dysfunctions, including decline in libido, erectile and orgasm dysfunctions (delayed orgasm, or inability to achieve orgasm), have been reported as an adverse effect of methadone and buprenorphine maintenance therapy [6, 7, 11]. The incidence of this type of sexual dys-

function is difficult to determine, and differs between countries. The use of opioids, especially in a long history of addiction, may cause a sexual dysfunction, and patients may decide to report this disability during methadone maintenance treatment. At this stage, when sexual symptoms are attributed to MMT by the patient, and are not satisfactorily addressed by the physician, adverse outcomes may occur. Use of Amphetamine and Cocaine, self-reduction of methadone dose, and interruption of MMT are some examples of self-treatment for sexual dysfunctions by these patients. Thus, consideration of sexual dysfunction as a drug side-effect is important because, besides caus-

Corresponding author: Shadan Tafreshian, Medical Doctor and Technical Manager of Methadone Clinic, Mashhad University of Medical Sciences, No 87, Moallem blv, 9188615119, Mashhad, Iran E-mail: [email protected]

49


ing difficulty in intimate relationships, it is likely to lead to an impairment of compliance with therapy, so interfering with the known benefits of methadone and buprenorphine. Other factors may come into play to give rise to sexual dysfunction in methadone-treated patients, such as hormonal phenomena (pathologies of the testicles, hypogonadism, dysfunction of the pituitary gland, hyperprolactinaemia), neurological, metabolic and arteriopathic causes; psychological factors (anxiety, depression, stress, pressure to perform), environmental problems (the couple, the family, and financial or professional issues), lack of information and ignorance about sexuality. In addicted patients, toxic causes are the main concern. It is well known that erectile dysfunctions are increased by tobacco use, and are twice as frequent with heavy smoking. Nicotine can cause atherosclerosis in the arteries of the penis, lesions of the endothelium of small blood vessels, vasoconstriction of the arteries of the penis, and contraction of smooth intracavernous muscular fibres, all leading to erectile dysfunctions. Furthermore, chronic alcoholism is a well-known cause of erectile dysfunction through its direct action on the testicles, or by leading to the hepatic degradation of testosterone. The chronic intake of cocaine is another possible cause of sexual dysfunction, as happens too with opioids [6]. Because there are only a few available studies on sexual dysfunction in opioid-addicted patients treated with methadone or buprenorphine, we designed a cross-sectional study with the aim of providing improved prevalence data for sexual dysfunctions in a sample of men on MMT or BMT in our country. 2.

for a sexual dysfunction, such as androgen replacement treatment. The sample consisted of 158 opioid-dependent male patients in maintenance treatment. Group A consisted of 102 MMT patients, and group B of 56 BMT patients. The mean age of our patients included in group A was 39 years (range: 23-64), and, for those in group B, was 33 years (range: 24-45). Average duration of methadone maintenance treatment was 122 months, and the mean methadone dose was 64 ± 2 mg/d. For patients on BMT the corresponding data were 92 months and 8 mg/d. 2.2. Instruments We collected socio-demographic data and investigated sexual function by using IIEF, an extensively validated questionnaire covering five domains of male sexual function: desire, erectile function, intercourse satisfaction, orgasm, and overall satisfaction [14]. We evaluated lack of libido, erectile dysfunction (difficulty in achieving or maintaining an erection) and difficulties in achieving orgasm. Patients' reports were collected and their responses were measured on the basis of an evaluation of their symptoms. Our patients were followed at least once a month by visits to physicians. By clinical assessment, further information was obtained on methadone or buprenorphine maintenance dose and length of therapy, use of other medications, evidence of other significant illnesses, recent alcohol use and tobacco smoking or other drug use such as benzodiazepines, cannabis, stimulants, or heroin supported by urine toxicology, according to our protocol. This study was approved by the Ethics Committee of the Mashhad University of Medical Sciences.

Methods 2.3. Data analysis

2.1. Sample The study included patients who had been registered in two Methadone Clinics in Mashhad, Iran (Saman and Mashregh Zamin Clinics), during a period of 18 months. All subjects gave written consent to their participation. These patients were self-referred for a medical evaluation of sexual dysfunctions associated with MMT/BMT, and were evaluated and treated by one of the authors. Patients were included in the study if they had been on MMT or BMT for at least one year, had a stable methadone/buprenorphine dose, and if they were free from any medical condition associated with organic sexual disability, such as diabetes. No patients had taken any medication - 50 -

Final data were evaluated statistically by using SPSS Software. Categorical variables were compared using the chi-squared test, and continuous variables were examined using regression analysis. For samples that were not normally distributed, the nonparametric T-test was used. All statistical tests were two-tailed, and a P value ≤ 0.001 was considered as statistically significant. 3.

Results

Demographic data, history of opioid use, abuse of other drugs or substances, and treatment details are shown in Table 1. With respect to loss of libido,

S. Tafreshian et al.: Sexual Dysfunction in Male Patients Receiving Methadone and Buprenorphine Maintenance Treatment in Iran

Table 1: Demographic and treatment details, history of opioid use, other drugs or substances

Number of men Age (mean years, range) Daily dose (mean mg/d ±SD) Duration of current continuous opioid treatment (mean value in months) Mean duration of opioid dependency (years ±SD) Method of taking drugs

MMT (Methadone maintenance therapy) group 102 39 (23-64) 64±2

BMT (Buprenorphine maintenance therapy) group 56 33 (24-45) 8±1

122

92

12±2

9±2

Oral 40

History of chronic and metabolic disorders History of depression Other regular substance use: Tobacco Alcohol Benzodiazepine Cannabis Stimulants Heroin

Smoking 24

Both of them 38

Oral 12

Smoking 12

Both of them 32

_

_

_

_

96 (94.1%) 7 (6.8%) 24 (23.5%) 2 (1.9%) 18 (17.6%) 12 (11.7%)

34 (60.7%) 6 (10.7%) 5 (8.9%) 9 (16%) 10 (17.8%) 20 (35.7%)

50.9% (52) of patients in MMT complained of a moderate to severe loss of libido, as against only 8.9% (5) in the BMT group. Patients in MMT, compared with patients in BMT, show a higher percentage of erectile dysfunction: 72.5 and 12.5% (74 and 7 patients), respectively; they showed more difficulty in achieving an orgasm, associated with a reduction in sexual satisfaction: 45% (23 patients) versus 3.5% (2 patients), respectively. According to the International

Index of Erectile Function domains (IIEF), the methadone group has significantly lower scores than the buprenorphine group in all domains (Table 2). 75% of patients in the BMT group report a moderate to high sexual drive, while the sexual life satisfaction scores are significantly higher in the BMT than in the MMT group (p<0.001). In both groups, erectile dysfunction seems to be a major component of sexual dysfunction. Thus, a significant correlation between treat-

Table 2: IIEF domain scores for men in treatment for addiction Methadone N = 102

IIEF Domain Scores Loss of libido (Number, Percentage)

52 (50.9%)

Erectile dysfunction (Number, Percentage)

74 (72.5%)

Intercourse: dissatisfaction (Number, Percentage)

44 (43.1%)

Orgasmic difficulties (Number, Percentage)

23 (45%)

Overall satisfaction (Number, Percentage)

24 (23.5%)

Max Score: 10 Score in this group: 5.1 Max Score: 30 Score in this group: 18.2 Max Score: 15 Score in this group: 6.8 Max Score: 10 Score in this group: 6.7 Max Score: 10 Score in this group: 5.9

Buprenorphine N = 56 5 (8.9%) 7 (12.5%) 5 (8.9%) 2 (3.5%) 42 (75%)

Max Score: 10 Score in this group: 8.1 Max Score: 30 Score in this group: 24.3 Max Score: 15 Score in this group: 11.2 Max Score: 10 Score in this group: 8.7 Max Score: 10 Score in this group: 7.5

IIEF = International Index of Erectile Function.

- 51 -


ment mode on one hand and ejaculation and erectile dysfunction on the other, can be observed. In addition, people on MMT have a high prevalence of sexual excitation and proneness to orgasm disturbances: 50.9% and 45%, respectively, compared with only 8.9% and 3.5% in the case of BMT. No valuable statistical correlation between duration of opioid use and sexual complaints was found in our two groups. The dose of methadone in MMT patients, in contrast with the BMT group, shows a significant role in sexual dysfunctions (p=0.011), and the duration of therapy is correlated with these complications (p=0.012). Most of our patients report change or no improvement in sexual function after treatment with methadone or with buprenorphine, compared with opioid use. 4.

Discussion

Methadone has been available for more than 35 years, and has been used by millions of patients in a variety of settings [8]. Buprenorphine is the other commonly used substance for the maintenance therapy of addicted patients. In clinical practice, buprenorphine is often used in patients who have a low level of opioid tolerance, and in patients whose doses are being reduced; methadone is indicated for patients with heavy or persistent opioid use, or with chronic pain. The frequency and the severity of side-effects seem to be similar for methadone and for buprenorphine users, although the claim has been made that quality of life is better in buprenorphine treatment [12]. Furthermore, in the list of the adverse effects of methadone, unlike those of buprenorphine, a reduction in libido and/or potency has been pointed out [5]. According to our results, the methadone group had significantly lower scores than the buprenorphine group in all domains of sexual function, but the recorded scores in buprenorphine are not fully reliable. In our study, in both groups (of methadone and buprenorphine users), erectile dysfunction seems to be a major cause of sexual dysfunction. According to earlier studies, erectile dysfunction (ED) usually has an organic or iatrogenic aetiology. A variety of systemic illnesses are associated with ED. These include chronic liver disease, renal failure, arteriosclerotic cardiovascular disease, diabetes mellitus, chronic obstructive pulmonary disease, and malignancy. Spinal trauma and genitourinary surgery are potential aetiological causes of ED, too [10]. Though more rare, congenital and other anatomic genitourinary anomalies (Peyronie’s disease, phimosis, post-traumatic aneurysm) should be considered [4]. None of our patients - 52 -

suffered from these diseases. Medications commonly associated with ED, which include antihypertensives, psychotropic agents and medications with anticholinergic effects, were not used by our patients. Mental and emotional health may be significant contributors to healthy sexual function, and depressive symptoms have been most strongly associated with ED, with 90% of men with severe depression reporting ED in one study [1]. Anxiety disorders has also been reported as causes of ED [15]. In our study, patients with psychiatric disorders were excluded from possible selection. So, except smoking, which is a strong risk factor for ED [13], in our study, ED seems to be a side-effect of opioid replacement treatment. Given the risk of sexual dysfunctions, physicians should screen patients who are receiving either methadone or buprenorphine replacement treatment, especially MMT patients. Spring et al. provided some evidence demonstrating a relationship between sexual dysfunction and methadone dose [16]. They found that men experiencing significant sexual dysfunctions were more likely to be on higher doses of methadone. In their study, however, men with a sexual dysfunction, in contrast with our records, endorsed a greater number of psychological symptoms that are important potential confounders for an effect due to a high methadone dose. Teusch et al. found MMT patients reporting reduced libido and orgasm dysfunction more frequently than controls, but the severity of dysfunction was unrelated to the methadone dose [17]. In a more recent study, Brown et al. demonstrated a link between methadone dose and orgasm dysfunction among 92 MMT patients on an average of 100 mg methadone daily [3]. The mean dose of methadone in our patients (64 mg/d) is significantly lower than the average methadone dose for the clinic as a whole (120mg/d). Most of the side-effects of drugs are dose-related. Naturally, patients will have fewer side effects when treated with homeopathic doses. This is not an indication to withhold effective doses. With methadone, as with any other medication, the management of sideeffects is preferable to the discontinuation of therapy. In summary, it is difficult to define the exact prevalence of sexual dysfunction in men on MMT compared with the general population. Despite this, we have attempted to consider other factors (depression, the use of other substances, age, treatment duration) which might play a role in symptoms of sexual dysfunction in MMT.

S. Tafreshian et al.: Sexual Dysfunction in Male Patients Receiving Methadone and Buprenorphine Maintenance Treatment in Iran

Limitations The feature that may limit the value of these results is that, in the present study, some of the characteristics of methadone and buprenorphine treatment differed, especially the duration of treatment. This factor could limit the significance of the multivariate analysis. 5.

Conclusions

In conclusion, buprenorphine may be less likely than methadone to cause sexual dysfunction; transferring from methadone to buprenorphine is one therapeutic option in cases where sexual dysfunction has been identified, as suggested by Bliesener et al [2]. It should, however, be borne in mind thattransferring from higher dose methadone may require prior dose reductions, and it is possible that methadone dose reductions will lead to the normalization of sexual function. So, further studies on sexual dysfunctions in opioid-treated patients should examine the potential benefits of methadone dose reductions, and the possible benefits of the reduction need to be weighed against the risks of continuing opioid use. References 1. Araujo A. B., Johannes C. B., Feldman H. A., Derby C. A., Mckinlay J. B. (2000): Relation between psychosocial risk factors and incident erectile dysfunction: prospective results from the Massachusetts Male Aging Study. Am J Epidemiol. 152(6): 533-541. 2. Bliesener N., Albrecht S., Schwager A., Weckbecker K., Lichtermann D., Klingmuller D. (2005): Plasma testosterone and sexual function in men receiving buprenorphine maintenance for opioid dependence. J Clin Endocrinol Metab. 90(1): 203-206. 3. Brown R., Balousek S., Mundt M., Fleming M. (2005): Methadone maintenance and male sexual dysfunction. J Addict Dis. 24(2): 91-106. 4. Brown R. T., Zueldorff M. (2007): Opioid Substitution with Methadone and Buprenorphine: Sexual Dysfunction as a Side Effect of Therapy. Heroin Addict Relat Clin Probl. 9(1): 35-44. 5. Cicero T. J., Bell R. D., Wiest W. G., Allison J. H., Polakoski K., Robins E. (1975): Function of the male sex organs in heroin and methadone users. N Engl J Med. 292(17): 882-887. 6. Déglon J. J., Martin J. L., Imer (2004): Methadone patients’ sexual dysfunctions: Clinical and treatment issues. Heroin Addict Relat Clin Probl. 6(3): 17-26. 7. Dyer K. R., White J. M. (1997): Patterns of symptom complaints in methadone maintenance patients. Addiction. 92(11): 1445-1455.

8. Espejo R., Hogben G., Stimmel B. (1973): Sexual performance of men on methadone maintenance. Proc Natl Conf Methadone Treat. 1: 490-493. 9. Hallinan R., Byrne A., Agho K., Mcmahon C., Tynan P., Attia J. (2008): Erectile dysfunction in men receiving methadone and buprenorphine maintenance treatment. J Sex Med. 5(3): 684-692. 10. Kandeel F. R., Koussa V. K., Swerdloff R. S. (2001): Male sexual function and its disorders: physiology, pathophysiology, clinical investigation, and treatment. Endocr Rev. 22(3): 342-388. 11. Paice J. A., Penn R. D., Ryan W. G. (1994): Altered sexual function and decreased testosterone in patients receiving intraspinal opioids. J Pain Symptom Manage. 9(2): 126-131. 12. Pende A., Musso N. R., Montaldi M. L., Pastorino G., Arzese M., Devilla L. (1986): Evaluation of the effects induced by four opiate drugs, with different affinities to opioid receptor subtypes, on anterior pituitary LH, TSH, PRL and GH secretion and on cortisol secretion in normal men. Biomed Pharmacother. 40(5): 178-182. 13. Rosen M. P., Greenfield A. J., Walker T. G., Grant P., Dubrow J., Bettmann M. A., Fried L. E., Goldstein I. (1991): Cigarette smoking: an independent risk factor for atherosclerosis in the hypogastric-cavernous arterial bed of men with arteriogenic impotence. J Urol. 145(4): 759-763. 14. Rosen R. C., Riley A., Wagner G., Osterloh I. H., Kirkpatrick J., Mishra A. (1997): The international index of erectile function (IIEF): a multidimensional scale for assessment of erectile dysfunction. Urology. 49(6): 822-830. 15. Sbrocco T., Weisberg R. B., Barlow D. H., Carter M. M. (1997): The conceptual relationship between panic disorder and male erectile dysfunction. J Sex Marital Ther. 23(3): 212-220. 16. Spring W. D., Jr., Willenbring M. L., Maddux T. L. (1992): Sexual dysfunction and psychological distress in methadone maintenance. Int J Addict. 27(11): 13251334. 17. Teusch L., Scherbaum N., Bohme H., Bender S., Eschmann-Mehl G., Gastpar M. (1995): Different patterns of sexual dysfunctions associated with psychiatric disorders and psychopharmacological treatment. Results of an investigation by semistructured interview of schizophrenic and neurotic patients and methadonesubstituted opiate addicts. Pharmacopsychiatry. 28(3): 84-92. Role of the funding source Authors state that this study was financed with internal funds. No sponsor played a role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

- 53 -


Contributors Authors contributed equally to this article. All authors revised and approved the final form of the manuscript. Conflict of interest Authors declared no conflict of interest.

Received June 27, 2013 - Accepted January 22, 2014 - 54 -


Outcomes of clonazepam maintained benzodiazepine-heroin addicted patients during methadone maintenance: A descriptive case series Angelo Giovanni Icro Maremmani 1,2, Silvia Bacciardi 1, Fabio Rugani 1, Luca Rovai 1, Enrico Massimetti 1, Denise Gazzarrini 1, Liliana Dell’Osso 5, Pier Paolo Pani 4, Matteo Pacini 1,3, and Icro Maremmani 1,2,3 1 Vincent P. Dole Dual Diagnosis Unit, Department of Neurosciences, Santa Chiara University Hospital, University of Pisa, Italy, EU 2 AU-CNS, Association for the Application of Neuroscientific Knowledge to Social Aims, Pietrasanta, Lucca, Italy, EU 3 G. De Lisio Institute of Behavioural Sciences Pisa, Italy, EU 4 Social and Health Services, Health District 8 (ASL 8) Cagliari, Italy, EU 5 Department of Experimental and Clinical Medicine, University of Pisa, Italy, EU

Summary Background. The use of benzodiazepine (BDZ) by patients on methadone maintenance treatment (MMT) has the effect of complicating the clinical picture. The relative safety of BDZ use by methadone- or buprenorphine-treated patients has still not been systematically examined. It is not yet clear whether a maintenance strategy with clonazepam is a useful BZD treatment modality for BZD-dependent MMT patients with a long-term history of abuse and previous attempts at detoxification. Methods. In this study our aim has been to collect and present detailed information regarding the outcomes of a small group of our patients who were treated with clonazepam maintenance during methadone maintenance. Results. In our sample of BZD-dependent MMT patients, who were treated with a methadone-clonazepam combination, the retention rate, at 8 years, was 57.1%. Baseline-endpoint improvements were significant for clinical global impression and the level of social adjustment. Conclusions. Patients with a severe comorbid dependence, when treated with over-standard dosages of methadone and co-treated with CMT, may have outcomes that are satisfactory as long as they are maintained on their medication in the long term. Key Words: Methadone Maintenance; Long-term Outcome; Benzodiazepines; Polyabuse; Clonazepam Maintenance

1.

Introduction

The use of benzodiazepine (BDZ) by patients on methadone maintenance treatment (MMT) has the effect of complicating the clinical picture and may negatively influence treatment outcomes (poorer psychosocial adjustment, higher levels of polydrug use, more risk-taking behaviours and a shorter retention in treatment) [8, 11, 14, 18, 48, 51]. A history of benzodiazepine prescription is significantly associated with drug-dependent death [40], and intermittent benzodiazepine abuse was found to be significantly associated with lower rates of opiate abstinence during methadone maintenance treatment [23]. Benzodiazepine MMT users are more likely to have injected recently, to have used cocaine and am-

phetamines, to have borrowed or lent used needles and syringes, and to have reported polydrug use in the preceding month. Benzodiazepine MMT users also exhibit higher levels of psychopathology and social dysfunction than other methadone maintenance patients. Benzodiazepine-using methadone maintenance patients are a dysfunctional subgroup of the methadone population, and they are likely to require more clinical intervention than other patients [13]. Some authors stress the high priority that should be given to stopping benzodiazepine use during [42] or before entering MMT. For example, the Stockholm Centre for Dependency Disorders has suggested that benzodiazepines should hardly ever be prescribed to patients on methadone/buprenorphine. Before entering MMT/buprenorphine treatment, the patient must

Corresponding author: Angelo Giovanni Icro Maremmani, MD; Vincent P. Dole Dual Diagnosis Unit, Department of Neurosciences, Santa Chiara University Hospital, University of Pisa, Via Roma, 67 56100 PISA, Italy, EU. E-mail: [email protected]

55


be negative for un-prescribed benzodiazepines, and, if a patient on MMT/buprenorphine becomes positive for benzodiazepines, the MMT/buprenorphine therapy should discontinued (Johan Franck, 2013 -personal communication). Others claim that cautiously prescribing benzodiazepines may be a beneficial strategy, due to the reduction of overall illicit use [14]. The relative safety of BDZ use by methadoneor buprenorphine-treated patients has still not been systematically examined. BDZs may significantly alter the response to opioid substitution treatment with methadone or buprenorphine. In any case, BDZ had greater peak effects on performance measures (simple reaction time, digit symbol substitution task, and cancellation time) in methadone-treated than in buprenorphine-treated patients [28]. Opiate/benzodiazepine co-dependent patients reported less severe withdrawal symptoms during treatment with buprenorphine than with methadone [44]. While methadone maintenance treatment (MMT) has been demonstrated to be an effective treatment for opiate dependence, its impact on the treatment outcome of other types of illicit drug abuse is not as clear. Therapeutic approaches for benzodiazepine (BZD) dependence in patients in methadone maintenance treatment (MMT) have met with limited success. Clonazepam detoxification (CDTX) and clonazepam maintenance treatment (CMT) have been experimented. Maintenance strategy with clonazepam is a useful BZD treatment modality for BZDdependent MMT patients with a long-term history of abuse and previous attempts at detoxification [55] Aims: In this study our objective was to collect and present detailed information about the outcomes of a small group of our patients who had been kept on clonazepam maintenance concomitantly with methadone maintenance, with special reference to our specific therapeutic context. 2.

Methods

2.1. Design of the study We designed an exploratory (or pilot) Case Studies project before implementing a large-scale investigation. The question we wished to study was the feasibility of CMT during MMT. We considered as relevant data the outcomes of our CMT-MMT patients. We collected data regarding their addiction history, and we continued to follow up the patients’ - 56 -

clinical situation and social adjustment over a period lasting between 1 and 7 years. Then we studied correlations between demographic and clinical aspects, on one hand, and patients’ survival in treatment time, on the other. 2.2. Setting In Italy, low-threshold facilities for drug addicts are available in each territorial district. When opioid agonists are employed in those settings, dosage and duration of treatment are usually limited, regardless of clinical indications [46, 47] that suggest the value of raising the dosage or extending the treatment [7, 10, 15, 43]. Patients are allowed to negotiate the lowering of dosages regardless of urinalyses, and to have their medication tapered earlier than would be advisable on the basis of the scientific literature. All the patients participating in the study were recruited from the Pisa Methadone Maintenance Treatment Programme (Pisa-MMTP), which belongs to the Pisa University Department of Psychiatry. Since 1993, the Pisa-MMTP has been using a clinical protocol that has the characteristics of a high-threshold treatment facility for opioid addiction focusing on pharmacological maintenance. After patients at the Pisa-MMTP have been safely inducted into treatment with methadone, their doses are gradually increased until the point is reached where there is no more than one urine drug screen which is positive for illicit opiates, cocaine, or benzodiazepines in the previous sixty-day period. Once this requirement is fulfilled, the patient is defined as having being “stabilized”, and the dose at which this goal has been accomplished is referred to as the “stabilization dose”. No upper limit for dosage exists. Despite this, one single time limitation is imposed in this setting: patients who cannot achieve stabilization within one year have to leave the programme, to be transferred to local treatment units. The dosage is increased to reflect the results of urinalyses, and evidence of improvement on social grounds is not enough by itself to justify dose stability as long as the urinalyses stay positive for opiates. Patients are not allowed to raise or lower the dose by themselves. Take-home doses, without limitations, and at most for a 7-day period, are allowed, once patients have shown complete compliance with the rules of the programme. Urine samples for toxicology analyses are collected randomly almost once a month, to allow evaluation of the metabolites of illicit drugs and benzodiazepines.

A.G.I. Maremmani et al.: Outcomes of Clonazepam Maintained Benzodiazepine-Heroin Addicted Patients During Methadone Maintenance: A Descriptive Case Series

In our programme, patients are required to become actively involved in treatment by attending the clinic whenever that is scheduled, participating in the development of their treatment plan, working towards treatment goals, meeting with medical and case management staff, and attending groups when needed. Patients with psychiatric comorbidity receive additional treatment with psychoactive drugs (mood stabilizers, antipsychotics or antidepressants) and supportive psychotherapy, as needed. In our clinical practice, BZD dependence is treated systematically, according to the following procedure, which is very similar to an agonist substitution approach. We started by switching the patient from the abused BZD to a slow-onset, long-acting, high potency BZD agonist – clonazepam. As the dosage of the abused benzodiazepine was progressively lowered, the clonazepam dosage was progressively raised until the substitution was complete. In this way the patient stopped his primary abuse of BZD without any switch from intoxication to withdrawal states. Afterwards, patients passed through four successive phases: induction, stabilization, maintenance, and, whenever possible, medication withdrawal. This methodology was recently described by Liebrenz et al. in BDZ-dependent patients [27]. For more information on this procedure, see Maremmani et al. [33] All the physicians working in the Pisa-Methadone Programmes are psychiatrists who have been trained for at least two years in the treatment of addictive disorders. 2.3. Sample We considered all the patients admitted to our programme over an 8-year time period (from January 1995 to May 2003) and enrolled in previous studies [31, 37]. We selected 14 patients diagnosed as heroindependent patients according to the DSM-IV-R diagnostic criteria (304.00); they also fulfilled DSM-IV criteria for severe dependence on sedatives, hypnotics or anxiolytics (F13.24). All these patients entered our CMT-MMT-programme and were followed up. 2.4. Instruments and procedure 2.4.1. DAH-Q, Drug Addiction History Questionnaire (administered at the beginning of treatment)

The DAH-Q [35] is a multidimensional questionnaire that comprises the following 8 areas: 1-demographic data, 2-physical health, 3-mental status,

4-social adjustment and environmental factors, 5-substances abused, 6-substance abuse modalities (heroin intake, modality of use, stages of illness, nosography), 7-treatment history and 8-addiction history (age at first contact, age at onset of continuous use, dependence length and age at first treatment). The Scale rates 10 presence-absence items: 1-somatic comorbidities, 2-abnormal mental status, 3-work problems, 4-household problems, 5-sexual problems, 6-socialization and leisure time problems, 7-drug-related legal problems, 8-polysubstance abuse, 9-previous treatment, 10-combined treatments. We encoded the modality of use as follows: 1-stables, 2-junkies, 3-two worlders, 4-loners, according to Lahmeyer’s classification [26]. “Stables” are opioid addicts who have adopted conventional values, hold legitimate jobs, are generally law-abiding and do not associate with other addicts. “Hustlers”, otherwise called “junkies” or “criminal addicts”, are closely identified with an addict subculture, are not legitimately employed, and subsist on the proceeds of criminal activities. “Two-worlder” addicts engage in criminal activities and associate with other addicts, but are also legitimately employed. “Loner” addicts are not involved either in the addict subculture or the conventional culture. They are usually unemployed, and live on welfare benefits rather than on the proceeds of criminal activities. These uninvolved addicts may have severe psychological disorders. The development of addiction may be considered to consist of three stages: 1-acute (immediate) drug effects (Honeymoon Stage); 2-transition from recreational use to patterns of use consistent with addiction (Increasing Dose Stage); and 3-end-stage addiction, which is characterized by an overwhelming desire to obtain the drug, a diminished ability to control drug-seeking and reduced pleasure from biological rewards (Revolving Door Stage) [22]. Considering the clinical typology, drug addicts can be divided into 1-reactive (presence of psychosocial stressors before using heroin), 2-self-therapeutic (presence of psychiatric stressors before using heroin), and 3-metabolic (no psychosocial or psychiatric antecedents) [38]. Regarding the pattern of use, data were recorded by us on whether the user of illicit opioids typically undergoes periods of voluntary or forced abstinence lasting weeks to months, followed by periods of relapse. For more details, see [29, 30, 32, 34, 36]. 2.4.2. Global Assessment of Functioning, DSM-IV-GAF (administered monthly).

The GAF considers psychological, social and occupational functioning within the sphere of a hypo- 57 -


thetical mental health-illness continuum, without including any impairment of functioning due to physical or environmental limitations. The point allocation follows a specific code, with a maximum of 100 and a minimum of 0, with the possibility of using intermediate codes if necessary [1]. 2.4.3. Clinical Global Impression (CGI) (administered monthly)

The CGI considers the severity of the disorder, the degree of the improvement or worsening following the intervention and any adverse reactions [21]. 2.4.4. Toxicological urine analyses (carried out randomly every week during the induction phase and almost every month during the stabilization phase)

The enzyme-multiplied immune technique for opiates was used. The toxicological urinalyses were expressed using two indices: PC-CU (per cent clean urines) and TS-CU (per total specimens clean urines). PC-CU represents the percentage ratio between urinalyses proving negative for the presence of morphine and the total number of urinalyses carried out for each patient during the treatment period. TS-CU is the percentage ratio between the number of urinalyses testing negative for the presence of morphine and the number of urine analyses that the protocol has envisaged throughout the process. In this case the reference number was 386 (the theoretical maximum number of urine samples per patient, considering an 8-year period). PC-CU tends to give a preference to patients who remain “opiate-free”, but who terminate the study in advance, for reasons not correlated with the study (for example, imprisonment). TS-CU also considers how long the patient remains in the protocol, but give priority to patients who show clean urine during a long-lasting treatment. These two indices represent the two extremes, and the results tend to balance out. 2.5. Data analysis Retention in treatment was analysed by means of the survival analysis. For the purpose of this analysis, the term ”terminal event” refers to patients who left the treatment as a “not stabilized patient” (see the section appearing above entitled “Setting” for details), while “withdrawing during interval” refers to patients who are still in treatment at the end-point, or leaving treatment for reasons unrelated to the treatment itself (e.g. patients moving to other towns, and periods of imprisonment for past crimes) or patients detoxified - 58 -

after the maintenance period. In other words, we consider 2 kinds of positive outcome: the first when a patient left the programme after successful detoxification (after the maintenance period) or was referred, as a “stabilized” patient, to other programmes, the second when a patient was still in treatment, at the endpoint, as a “stabilized” patient. We consider it to be a negative outcome when a patient has failed to achieve stabilization within a year or has relapsed into addictive behaviour after a period of stabilization. The association between demographic and clinical variables and retention in treatment, adjusting for potential confounding factors, was summarized using Cox regression. Differences in demographic and outcomes measures were analysed by applying the general linear model, repeated measure methodology, and adjusting for outcome. 3.

Results

3.1. Demographic characteristics addiction history

and

heroin-

Mean age was 30.14±3.8 (range: 26-38). 14 (71.4%) were males and 4 (28.6%) females. 5 (35.7%) were highly educated people (with over 8 years of education) and 9 (64.3%) had a low level of education. 12 (85.7%) were single and only 2 (14.3%) had a partner. 2 (14.3%) had a white collar job and 3 (21.4%) had a blue collar one, 9 (64.3%) were unemployed. Low income was found in 1 (7.1%) subject, and adequate income (sufficient to satisfy a requirement or meet a need) in 13 (92.9%) subjects. 13 (92.9%) had an urban birth location and 11 (78.6%) were living in an urban zone. Only 2 (14.3%) subjects were living alone. All patients were recruited in Central Italy. At treatment entry, at least one of the somatic complications that were investigated (hepatic, vascular, lymphatic, gastrointestinal, sexual, dental, HIV+, AIDS) was observed in 13 (92.9%) subjects. Mean was 2.28±1.5 (0-6 ranged). At least one of the mental status areas that were investigated (insight, consciousness, memory, anxiety, depression, sleep, eating, excitement, violence, suicidality, delusions and hallucinations) was found to be altered in all subjects. Mean was 6.28±1.6 (4-10 ranged). Only 3 (21.4%) subjects were enjoyed their job; 5 (35.7%) were unsatisfied with their household relationship; 6 (42.9%) with their erotic situation; 12 (85.7) with their socialleisure activities. 8 (57.1%) reported current or past legal problems. Polyabuse (more than 3 substances of


abuse) was occasionally present in 10 (71.4%) subjects. Mean number of occasionally abused substances was 3.57±1.6 (range: 1-6). Only 2 (14.3%) patients had never been treated. Mean number of past different kinds of treatment was 2.71±1.8 (range: 0-6). We investigated 12 different kinds of treatment: therapeutic community, psychopharmacology, psychotherapy, short-term detoxification with opioid agonists, partial agonists and antagonists, maintenance treatment with opioid agonists, partial agonists and antagonists. As to comorbid substance use, 9 (64.3%) patients occasionally used alcohol, 10 (71.4%) CNSstimulants, 11 (78.6%) cannabinoids, 10 (71.4%) hallucinogens and 1 (7.1%) inhalants. Heroin intake took place at least once a day in 11 (78.6%) patients. Modality of heroin use was unstable in 12 (85.7%), periodic self-detoxification occurred in 10 (71.4%), Stage 3 of heroin addiction was reached by 11 (78.6%), psychosocial stressors, before starting heroin, were present in 4 (28.6%). Mean age at first heroin use was 20.57±4.8 (range: 14-31), mean age at start of continuous heroin use was 22.29±4.4 (15-31), mean age, at 1st treatment, was 25.64±4.4 (17-33) years. Mean dependence length (months) was 79.79±70.1 (range:

12-240). At treatment entry, mean dose of abused BZD (expressed as diazepam-equivalents) was 166.78±57.6 mg/daily (range: 100-250). 11 (78.6%) patients were using between 100 and 200 diazepam-equivalent mg/ daily, 3 (21.4%) over 200 mg/daily. Severity of illness was considered moderate in 3 (21.4%), marked in 7 (50.0%) and severe in 4 (28.6%) patients. Global assessment of functioning classified 4 (28.6%) subjects in cluster 3 (inability to function in almost all areas (e.g., staying in bed all day; no job, home, or friends); 3 (21.4%) in cluster 4 (major impairment in several areas, such as work or school, family relations, judgment, thinking, or mood); 5 (35.7%) in cluster 5 (any serious impairment in social, occupational, or school functioning (e.g., no friends, unable to keep a job); only 2 (14.2%) showed a better than described social adjustment. 3.2. Survival in treatment At start of the first year we had 14 subjects in treatment. During the first year there was one terminal event (0.07%) with a survival index of 0.93. At

1$ 0.90$

Cumula&ve)survival)rate))

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0.64$ 0.64$

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1+2$yrs$ 13)

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0.56$

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6+7$yrs$

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Figure 1. Survival in treatment of 14 clonazepam maintained benzodiazepine-heroin addicted patients during Methadone Maintenance

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Table 1. Outcomes (baseline-endpoint) in clonazepam-maintained patients during methadone maintenance according to the outcome Measures N Outcome M±sd CGI (baseline) 6 Negative 5.17±0.7 8 Positive 5.00±0.7 CGI (end-point) 6 Negative 2.58±0.9 8 Positive 1.50±0.7 DSM-IV-R GAF (baseline) 6 Negative 43.33± 8.1 8 Positive 45.00±15.1 DSM-IV-R GAF (end-point) 6 Negative 71.66± 4.0 8 Positive 82.50 ±7.0 Multivariate tests: time effect: F137.49, p<0.001; time-outcome effect: F=3.04, p=0.089

Statistics Source Time Time-outcome

Measure CGI DSM-IV-R GAF CGI DSM-IV-R GAF

Time Level 2 vs level 1 Level 2 vs level 1 Level 2 vs level 1 Level 2 vs level 1

the start of second year we had 13 in-treatment patients. During this year there were 4 (31%) terminal events, with a fall in the cumulative survival index to 0.64. At the start of third year we had 9 in-treatment patients. During the 3rd year one patient successfully terminated the treatment by leaving the programme in an opioid-detoxified condition and without BZD. No terminal events were observed. At the start of the 4th year 8 patients were in treatment. During the 4th year one (13%) terminal event was observed, and the cumulative survival index fell to 0.56. At the start of the 5th year 7 patients were in treatment. During the 5th year one patient successfully terminated the programme, in an opioid-detoxified condition and taking only a small amount of clonazepam (2mg/daily in two doses). No terminal events were observed during the 6th or 7th years of treatment, the cumulative survival index remaining at 0.56. At the end of the 7th year, 6 patients were still in treatment. Figure 1 summarizes the situation for the survival in treatment of our patients. In summary, the outcome was ‘negative’ in 6 (42.9%) subjects and ‘positive’ in 8 (57.1%). No patient with a ‘negative’ outcome voluntarily abandoned the programme, whether for side-effects, altered bio exams, imprisonment, hospitalization or death. All negative-outcome patients lost their status as a ‘stabilized patient’ and were transferred to lowthreshold programmes. Using Cox regression, only the opiate PC-CU index significantly predicted survival in treatment (Chi-square =12.43, df=1, p<0.001; Exp(B)=0.001, CI95%: 0.001-0.079).

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F 266.72 73.28 6.05 1.42

df 1 1 1 1

P <0.001 <0.001 0.030 0.256

3.3. Baseline-end point changes Multivariate tests showed that CGI severity of illness and DSM-IV GAF (global assessment of functioning) demonstrated significant improvements in our patients independently of their outcome. For details see table 1. 3.3. Medication dosages On average, patients with severe comorbid BDZ dependence needed an over-standard methadone dosage in the stabilization phase (190.73±103.4 mg/day). Patients who had a positive outcome did not receive different stabilization dosages (Student’s T-test=0.55, p=0.586). The clonazepam stabilization dosage was 21.36±7.2 mg/daily (min 12.50, max 32.50. 3.5. Urinalyses After eliminating from the analysis the toxicological examination performed at the time of enrolment in the programme (which was required to be positive), 2,947 urine samples were analysed in all. Of these, 2,554 (86.6%) were opiate-clean. In positive-outcome patients the opiate PC-CU index was 0.90±0.05; in negative-outcome patients, it was 0.64±0.1 (Student’s T-test =5.81, p=<0.01). The opiate TS-CU index revealed differences (T=5.97; p<0.001) between positive (0.73±0.2) and negative (0.12±0.6) outcome.


4.

Discussion

We examined treatment retention and outcomes for clonazepam-maintained patients during methadone maintenance. We observed that: Patients were assessed at baseline, in terms of somatic and psychopathological complications, frequency of unsatisfactory social and leisure time, and the presence of polyabuse. These data are in agreement with the observations of Drake et al. [13] on whether MMT patients with BDZ dependence can be considered to belong to a dysfunctional group. However, the characteristics found by us did not appear to be related to the patients’ retention or their outcome. Patients with concomitant severe BDZ dependence were recorded as having been successfully retained in long-term treatment; they showed good results for opiate-negative urine specimens; they required over-standard doses of methadone. In particular, the outcome and the percentage figures for retention in therapy of our patients did not differ from those of long-term standard MMT programmes [5, 12, 16, 25, 50, 52]. The main difference between our programme and standard Italian MMT lies in the amount of methadone administered during the stabilization phase; this ranges from 80 to 400 mg/day in our protocols and from 40 to 100 mg/day in standard protocols. A possible explanation for the need for these relatively higher doses in BDZ dependentpatients may be related to a pharmacokinetic and/or pharmacodynamic mechanism. Methadone is metabolized in the liver by the P450 cytochrome system and, more specifically, by the CYP3A4 isoform, which is involved in the metabolism of over 50% of the medical agents [9, 17]. The wide inter-individual variability [3, 24, 49, 53, 54, 56] recorded, and the fact that CYP3A4 can be induced by several active principles [20, 41], may explain why a number of patients are under-medicated if a standard dose of methadone is used. Unfortunately we did not measure plasma methadone levels in our patients during the stabilization phase, so we cannot determine whether the doses used were necessary to maintain a proper therapeutic window or to control an underlying underestimated psychopathology. In our patients the existence of a minor form of psychopathology in the other patients concealed under the main addictive symptoms cannot be excluded. There is significant overlapping between behaviours in some types of psychiatric disorders and drug-relat-

ed behaviours: maladaptive behaviours, such as those commonly displayed by drug-addicts, may sometimes be due to, or accentuated by, concurrent psychiatric disorders. Thus, a low degree of compliance with therapies is a common symptom of drug addiction and of several forms of psychiatric disorders [4, 6, 19, 45]. In addition, we found that the outcome of MMT patients with or without dual diagnosis is the same in the short [39] and long term [37]. The low CGI score and the high GAF score values recorded for our patients and the absence of hospitalizations throughout the treatment period showed that these subjects were simultaneously compliant both with MMT requirements and with the specific benzodiazepine therapy adopted. Cox regression suggests that the effectiveness of methadone treatment supports the results obtained with methadone-clonazepam combined treatment. Additional clonazepam for the treatment of benzodiazepine abuse – medication not completely changed by the need to treat addiction – may partly explain the positive outcomes obtained in our comorbid patients, which cannot be attributed exclusively to the effects of methadone. A lack, whether of appropriately flexible methadone doses and/or of specific medications given in association with methadone treatment for these patients, could have been responsible for the conflicting results obtained by other researchers, who reported that benzodiazepine and alcohol abuse were linked to worse treatment outcomes (retention in treatment) [8, 11, 14, 18, 48, 51]. In addition, the psychotherapeutic support provided by our team and the high therapeutic pressure of our programme could have been responsible for good results [2]. Limitations In any case, the incisiveness of our study was limited by several factors, such as the observational nature of the protocol, the impossibility of evaluating a follow-up in the case of the patients who dropped out, the multiple interference caused by inter-individual variability (personality traits and their neurobiological correlates), the clinical setting and the temporary use of adjunctive medications. We therefore chose this kind of research because of the fact that we had little control over events, and there was a contemporary focus within a real life context. The goal of our case study is to offer new points of view and questions for further research, considering that 35% of patients who enter methadone treatment can be described as “regular/problem users” [8]. - 61 -


5.

Conclusions

We can stress that patients with severe comorbid BDZ dependence, if they are treated with over-standard dosages of methadone and co-treated with CMT, may have outcomes that are satisfactory as long as they are maintained on their medication in the long term. References 1. A.P.A. (1994): Diagnostic and Statistical Manual of Mental Disorders, DSM-IV. American Psychiatric Association, Washington. 2. Amato L., Minozzi S., Davoli M., Vecchi S. (2011): Psychosocial and pharmacological treatments versus pharmacological treatments for opioid detoxification. Cochrane Database Syst Rev. 9: CD005031. 3. Änggård E. (1974): Disposition of Methadone in Methadone Maintenance. Clin Pharmacol Ther. 17(3): 258-266. 4. Baigent M. (2012): Managing patients with dual diagnosis in psychiatric practice. Curr Opin Psychiatry. 25(3): 201-205. 5. Blaney T., Craig R. J. (1999): Methadone maintenance. Does dose determine differences in outcome? J Subst Abuse Treat. 16(3): 221-228. 6. Brady K. T., Sonne S. C. (1995): The relationship between substance abuse and bipolar disorder. J Clin Psichiatry. 56(3): 19-24. 7. Brady T. M., Salvucci S., Sverdlov L. S., Male A., Kyeyune H., Sikali E., Desale S.,Yu P. (2005): Methadone dosage and retention: an examination of the 60 mg/day threshold. J Addict Dis. 24(3): 23-47. 8. Brands B., Blake J., Marsh D. C., Sproule B., Jeyapalan R., Li S. (2008): The impact of benzodiazepine use on methadone maintenance treatment outcomes. J Addict Dis. 27(3): 37-48. 9. Chen C. H., Wang S. C., Tsou H. H., Ho I. K., Tian J. N., Yu C. J., Hsiao C. F., Chou S. Y., Lin Y. F., Fang K. C., Huang C. L., Su L. W., Fang Y. C., Liu M. L., Lin K. M., Hsu Y. T., Liu S. C., Chen A., Liu Y. L. (2011): Genetic polymorphisms in CYP3A4 are associated with withdrawal symptoms and adverse reactions in methadone maintenance patients. Pharmacogenomics. 12(10): 1397-1406. 10. D’ippoliti D., Davoli M., Perucci C. A., Pasqualini F., Bargagli A. M. (1998): Retention in treatment of heroin users in Italy: the role of treatment type and of methadone maintenance dosage. Drug Alcohol Depend. 52(2): 167-171. 11. Demaria P. A., Jr., Sterling R., Weinstein S. P. (2000): The effect of stimulant and sedative use on treatment outcome of patients admitted to methadone maintenance treatment. Am J Addict. 9(2): 145-153.

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Role of the funding source Authors states that this study was financed with internal funds. No sponsor played a role in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication. Contributors AGIM, SB, FR, LR, and IM revised literature and conceived the methodology of the study (sample selection, statistical analyses) discussed results and wrote the preliminary report. EM, LDO, PPP, MP discussed results. All authors revised and approved the final form of the manuscript. Conflict of interest Authors declared no conflict of interest. IM served as Board Member for Reckitt Benckiser Pharmaceuticals, Mundipharma, D&A Pharma, and Lundbeck.

Received February 2, 2013 - Accepted April 18, 2014 - 64 -


Gender differences in severity of addiction in opiate-dependent outpatients Marcela Mezzatesta-Gava 2, Carlos Roncero 1,2, Laia Rodriguez-Cintas 1,2, Gideoni Fuste 1,2,3, Carmen Barral 1,2, Nieves Martinez-Luna 1,2, Miquel Casas 1,2, and Laia Miquel 1,2,4 1 Outpatients drug clinic (CAS) Vall d’Hebron, Hospital Universitari Vall d’Hebron, Agencia de Salut Pública de Barcelona (ASPB), Spain, EU 2 Department of Psychiatry. Hospital Universitari Vall d’Hebron. CIBERSAM. Universitat Autònoma de Barcelona, Spain, EU 3 Private Practice, A Coruña, Spain, EU 4 Network Group for Research in Woman Mental Health (GTRD).

Summary Background. Opioid dependence is a prevalent health problem. The literature now available on how to achieve a better knowledge of how this problem affects women, and on the importance of gender differences, is still limited. Aim. The aim of this study was to characterize gender differences in socio-demographic features, clinical manifestations, comorbid disorders and severity of opiate addiction, so as to define the role of gender differences in the severity of the addiction. Methods. A cross-sectional, observational, descriptive study evaluated a total of 124 opiate-dependent patients seeking treatment from an urban outpatient programme. Both Axis I and Axis II diagnoses were assessed by applying the Structured Clinical Interview for DSM Disorders I and II (SCID-I and SCID-II). The severity of addiction was evaluated through the application of the European Addiction Severity Index (EuropASI) instrument. Results. Women experienced a stronger impact from opioid addiction on their employment status, considering that the risk of presenting a severe ASI composite score was 4.4 times higher than the risk for men (IC95% 1.3-15.1). Females had a higher likelihood of being diagnosed with an affective disorder. Men showed a greater duration of regular heroin use, and were more likely to meet the current criteria for alcohol dependence; these data correlated with a higher severity of the related ASI composite score (OR=3.8 (IC95% 1.1-13.5)). Conclusions. Significant differences in the severity of addiction, substance use profile, psychiatric comorbidity and areas of impaired functioning were found to be due to gender differences. Key Words: Drug Use; Gender Differences; Mental Health; Heroin; Psychiatric Comorbidities

1.

Introduction

Opioid abuse and dependence is a health problem that necessarily raises deep concerns. During the last few decades, efforts have been made to achieve a better knowledge and understanding of how this problem affects women and gender differences. Initially, substance use disorders were classified as a male problem, and most studies were focused on male populations [34]. As a result, the available literature on the severity of opiate addiction in women is still limited. Severity of addiction has been related to the presence of other psychiatric conditions – age at onset of drug use, polydrug use, and so on. Previous studies have shown that 34.2-83% of patients with

opiate dependence have one or even more comorbid psychiatric disorders [16, 23, 28, 31]. Furthermore, numerous studies have concluded that female opioid users are more likely to exhibit higher levels of psychological distress [7, 16, 26, 31, 32]. In 2007, for example, Shu-Chuan found that 37.5% of female opiate dependents had another axis I diagnostic, compared with 11% for the male participants. Consistent findings about higher rates of depression in women have been described [1, 27]. However, data related to anxiety disorders such as specific phobia [31], posttraumatic stress disorder (PTSD) [27] or eating disorders [27] are contradictory [6, 16, 31]. Personality disorders (PD) are very frequent in opiate-dependent patients (from 19 to 80%) [8, 11, 22] and their prevalence does not differ between

Corresponding author: Marcela Mezzatesta-Gava, Department of Psychiatry. Hospital Universitari Vall d’Hebron. CIBERSAM. Universitat Autònoma de Barcelona, Passeig de la Vall D'Hebrón 35, 08035, Barcelona, Barcelona, Spain; Phone: + 34 934893880; Fax: + 34 934893880; Mobile: +34692609890; E-mail: [email protected]

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the sexes [16]. However, gender differences in the type of PD were detected. While men had significantly more Antisocial Personality disorders [16, 27], female subjects were more commonly diagnosed with Borderline Personality disorder [27] and were twice as likely as men to suffer from Paranoid Personality disorder [16]. In most studies, the ASI instrument has shown that opiate-dependent women experienced more severe effects in their employment status [2, 15, 20], and in the medical [2, 10, 15, 19, 20] and psychiatric areas [2, 10, 15, 19, 20], whereas men were more susceptible to legal problems [2, 27]. In any case, contradictory data still exist in the family & social [2, 33], alcohol [2] and drug areas [2, 10]. These differences might be due to different treatment settings and/or cultural differences. Even though consistent findings exist, there is still a lack of knowledge on differences in severity that are due to gender in some areas of importance. In planning treatment, it is important to know whether gender differences exist, and which areas of functioning should be acted upon to achieve better outcomes. The present study aims to develop previous research by specifying gender differences in terms of the severity of the addiction, and describing which functional areas are most affected in an opiate-dependent sample recruited from an outpatient programme in a drug treatment setting. 2.

Methods

2.1. Design of the study We performed a cross-sectional, observational study. The participants were patients that were attending the outpatient drug clinic at the Vall d'Hebron University Hospital (Barcelona, Spain). The research was approved by the Ethics Committee at the Vall d'Hebron Hospital. This study is part of a more extensive research project on comorbidity in drug-dependent outpatients. 2.2. Sample Inclusion criteria were: age over 18, opiate dependence according to DSM-IV criteria, and signing an informed consent document prior to participation. Exclusion criteria were: intoxication at baseline examination, severe somatic disease at baseline examination and low language proficiency. Patients did not receive any financial compensation for participating - 66 -

in this study. Participants attending an outpatient programme for opiate dependence were recruited consecutively from 2006 until 2011. These patients had been referred from primary care settings, the psychiatry emergency department or from inpatient units. 269 patients seeking treatment for opiate dependence were accepted. Of those, only 124 patients provided written informed consent prior to any study procedures. The evaluation process consisted initially in a mental examination by a psychiatrist, followed by three interview sessions conducted by trained psychologists. 2.3. Instruments Sociodemographics and clinical data were recalled with a questionnaire designed ad hoc with this proposal fulfilled by patients at the moment of admission. The Spanish version of the European Addiction Severity Index was used [3,4] to assess the severity of opiate addiction. This is a relatively brief, semistructured interview designed to provide important information about aspects of a client’s life that may contribute to his/her substance abuse syndrome. It measures several domains: medical status, alcohol and drug use, employment and support status, family and social relationships, legal status and psychiatric status. The EuropASI is an adaptation of the fifth version of the Addiction Severity Index [12,13]. It is one of the most widely used assessment and diagnostic tools in Europe. As the European Addiction Severity Index was the first psychological evaluation administered, no dropouts were registered. Diagnoses in Axis I were assessed by the Structured Clinical Interview for DSM Disorders, SCID-I; this instrument ensures a good level of agreement between interviewers, with a Kappa value of 0.70 to 1 [13]. Axis I diagnoses other than Substance Use Disorders were studied, including Major Depression, Adjustment Disorders, Bipolar Disorders, Anxiety, and Psychotic Disorders. Dual diagnosis was considered when patients had an Axis I or II diagnosis other than SUD. Personality disorders were evaluated through SCID-II; in assessing the degree of agreement between interviewers, we found a Kappa value of 0.74 to 0.87 [12]. Personality disorders were classified in 3 groups: Cluster A (paranoid, schizoid or schizotypal), Cluster B (histrionic, narcissist, borderline or antisocial), and Cluster C (avoidant, obsessive-compulsive and dependent). Drug use assessment included mainly opiates and alcohol, and then other drugs such as cannabis, amphetamines and cocaine.

M. Mezzatesta et al.: Gender Differences in Severity of Addiction in Opiate-Dependent Outpatients

2.4. Data analysis Statistical descriptive analyses were carried out for sociodemographic and clinical data in terms of frequencies, means and standard deviation. Normality assumptions were verified using the KolmogorovSmirnov test. The ASI composite score was transformed into a binary variable due to its irregular distribution. The median of each ASI composite score for the whole study sample was used as the cut-off to distinguish between severe and non-severe problem areas included within the composite score (ASI: Medical >0.255; Employment >0.69; Alcohol > 0.05; Drugs >0.263; Legal >0; Family and Social >0.31; Psychiatric >0.36). The relationship between categorical variables was investigated by using the χ2 Pearson test. When the expected frequency was lower than 5, Fisher´s exact test was applied, as happened with the following variables: Antisocial Personality disorder and cluster C PD. T-tests were used to examine quantitative measures by gender. All statistical tests were two-sided. The statistical difference for all tests was set at p values less than or equal to 0.05. A multiple logistic regression was carried out with gender as the dependent variable. The objective was to determine the relationship between gender and the Addiction Severity Index, after adjusting for alcohol dependence and the mean length of years of regular use of opiates. Variables in which gender differences reached statistical significance in the univariate analysis, and could, theoretically, act as confounding factors, were included in the logistical regression as covariates. The Statistical Package for Social Sciences (SSPS 18.0) was used for data analysis. 3.

Results

higher for women than for men (Men: median 0 children, range (0-2) vs Women: Median 1, range (0-3); t= 2.7, p=0.009). 3.2. Gender differences in substance use profile At the time of the evaluation, 30% of patients reported active opiate consumption. Out of the 70% that were abstinent, 30% had sustained abstinence for a brief period, while the remaining 40% had been able to sustain abstinence for over a month. In addition, 48.4% of the sample had a daily use of opiates, 34.4% were abstinent and 17.2% consumed once a week or less, but no gender differences were observed. The most frequently used route of administration was intravenous (56.6%). The mean length of regular use was higher in men than in women: 12.8 (SD 9.1) years vs. 8.4 (SD 6.8) years (t= 2.6, p=0.047). Men were more likely to meet the criteria for alcohol dependence than female participants (40.4% vs 14.3%; χ2 = 5.9, p= 0.015). Abuse of sedatives and dependence on them were higher in women. At least 14.8 % of the female sample abused benzodiazepines, against 10.5% of their male counterparts. Similarly, women showed a stronger tendency to depend on sedatives than their male counterparts (39.3% vs. 21.1%), although this difference was not at a significant level. 3.3. Medical comorbidity 69.1% of the total sample presented at least one medical comorbidity. 47.2% of the sample were affected by an infectious disease and 49% presented a history of hepatic disease (including Hepatitis C). Even though no significant differences were detected, 78.8% of women reported a previous medical record vs. 65.6% of the male sample.

3.1. Description of the sample:

3.4. Other Psychiatric Diagnoses

A total of 124 patients (27.4% women) were evaluated. The mean age of the whole sample was 37.7 years (S.D. 8.0). Table 1 shows sociodemographic and clinical gender differences. No significant differences between genders were observed in the sociodemographic features except for marital status. Half of the women in the sample were married, 41.2% were single, and only 8.8% divorced. On the other hand, most men were single (47.2%), 21.8% were married or lived with a partner, and 24.7% had divorced (χ2= 6.7; p=0.0035). The mean number of children was

Regarding Axis I, the female group showed a greater likelihood of being diagnosed with a Major Depressive Disorder (χ2= 5.04, p=0.024) or an Anxiety Disorder (χ2= 6.04, p=0.014) (Table 1). In addition, with reference to Personality Disorders, 41.9% were diagnosed with a cluster B Personality Disorder. Moreover, 40% of the males in the sample presented Antisocial Personality Disorder, compared with 20% of women (F=3.7, p=0.055). Furthermore, 4.3 % of the sample met the criteria for cluster A Personality Disorder and 5.4% were suffering from a cluster C Personality Disorder, with a - 67 -


Table 1. Sociodemographic and clinical characteristics by sex

n

Men

Women

n=90

n=34 %

n

%

Academic Level Uncompleted Primary School

18

20.2

9

26.5

Completed Primary School

27

30.3

9

26.5

Secondary School

38

42.7

15

44.1

6

6.7

1

2.9

University Marital Status Single

42

47.2

14

41.2

Married/Stable Couple

25

28.1

17

50

Separated/Divorced

22

24.7

3

8.8

Employment Status Employed

13

14.8

5

14.7

Unemployed

40

45.5

13

38.2

Pensioner/Sick leave

18

20.5

5

14.7

Other

17

19.3

11

32.4

Mean

SD

Mean

SD

χ2

p

1.19

0.75

6.7

0.03

2.54

0.46

t

p

Opioids Use profile Age at onset

20.8

6.8

20.9

7.2

0.25

0.8

Age at regular use

22.9

6.9

22.9

8.7

0.46

0.6

Years of regular use

12.8

9.1

8.4

6.8

2.63

0.01

n

Route of administration Intravenous Intranasal

%

n

%

52

57.3

18

54.5

23

25.8

5

12.1

2

χ

p

0.08

0.02

Smoked Other Current pattern of drug use Daily Several times per week Once a week Others Abstinence during evaluation

15 0

16.9 0

8 3

24.2 9.1

34 10 5 14 35

37.1 11.2 5.6 15.7 71.4

13 3 0 2 16

39.4 9.1 0 6.1 69.6

0.08

0.25

0.02

0.87

Previous treatment

77

85.4

26

73.5

0.12

0.29

Overdose episodes

36

41.9%

12

35.3%

0.51

0.54

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Table 1. Sociodemographic and clinical characteristics by sex Men

Women

n=90

n=34

n

%

N

%

p

χ2

Co-morbid substance use Alcohol Dependence

23

40.4

4

14.3

5.8

0.01

Sedatives Dependence

12

21.1

11

39.3

3.16

0.07

Cannabis Dependence

16

28.1

6

21.4

0.43

0.51

Cocaine Dependence

40

70.2

18

64.3

0.30

0.58

Psychiatric History

52

58.4

17

51.5

0.46

0.49

Dual Diagnosis

55

61

15

44.1

2.89

0.08

Bipolar Disorders

2

3.5

0

0

1.06

0.31

Depressive Disorders

3

5.4

6

21.4

5.04

0.02

Anxiety Disorders

6

10.5

9

3.21

6.03

0.01

Psychotic Disorders

1

1.8

0

0

0.49

0.48

Cluster A PD

3

4.7

1

3.4

0.07

0.78

Cluster B PD

29

45.3

10

34.5

0.96

0.32

Cluster C PD

1

1.6

4

13.8

5.86

0.01

Medical Comorbidity

31

34.4

7

21.2

1.98

0.15

Infectious Diseases

43

47.8

15

45.5

0.05

0.82

Hepatic Diseases

32

45.1

18

58.1

1.45

0.22

higher percentage recorded for women (1.6% men vs. 13.8% women) (F=5.6, p= 0.032). 3.5. Gender differences in severity of addiction Data on gender differences in the severity of these problem areas (medical status, employment/ support status, alcohol and drug use, legal status, family/social relationships and psychiatric status) are shown in Table 2. Regarding the composite employment total, women experienced greater severity in this problem area than men (67.6% vs 41.1%). Even though the differences in employment status were not significant, after adjusting for alcohol dependence and years of regular opiate use, women had an OR=4.4 (IC95% 1.3-15.1) of having a severe setback in the ASI employment status problem area, a figure higher than that for men (Table 3). On the other hand, men showed greater severity in the alcohol use problem area, as almost 51.1%

of men, vs 29.4% of women, had a severe repercussion χ2= 4.7, p=0.03). After adjusting for confounding factors, opiate-dependent men had 3.8 times more risk of having a higher score in the ASI alcohol composite score (IC95% 1.1-13.5) (Table 3). Moreover, despite the fact that no significant differences were found, men showed more problems in the legal status problem area (38.9% of men vs 23.5% of women). No statistically significant differences were observed in drug status, medical status, psychiatric status or in the family and social relationships composite scores recorded for the ASI, although these areas were found to be severely affected in around half of the sample (Table 2). 4.

Discussion

The present study examined gender differences in the severity of opiate dependence among 124 opioid-dependent outpatients seeking treatment. We only

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Table 2. ASI composite scores in terms of severity by sex. Severe Composite Medical Employment Alcohol Drugs Legal Family and social Psychiatric

Men n 39 37 46 44 35 44 43

Women % 43.3 41.1 51.1 48.9 38.9 48.9 47.8

found gender differences in the severity of employment and alcohol areas. Women experienced greater repercussions in the employment area, whereas men had a more severe impact in the alcohol area. Consistently with previous studies of treatmentseeking inpatient and outpatient samples, less than one-third (27.4%) of the current sample were women [3, 4, 16, 17, 29, 33]. No differences in sociodemographic features were found, in contrast with other studies, where fewer women, percentagewise, were found to be divorced or separated, widowed, living with their children and unemployed [4, 7, 16, 17, 30, 31, 33]. Despite there being no evidence of gender differences in the sociodemographic data related to employment aspects, women showed greater severity in the repercussions on this problem area, as revealed by a higher ASI composite score. This inconsistency might be due to the role that having a driving licence plays in the ASI’s employment status composite score, since, in our environment, using public transport is a common way of travelling to work, and not having a driving licence is not a major obstacle to working. This kind of item was not included in the sociodemographic questionnaire, which was mainly focused on working status. As to the substance use profile, the only statistically significant gender differences found were those

n 19 23 10 18 8 18 16

% 55.9 67.6 29.4 52.9 23.5 52.9 47.1

c2 1.7 7.0 4.7 0.2 2.6 0.2 0.01

p-value 0.2 0.008 0.03 0.7 0.1 0.7 0.9

on the length of regular use, with men having a longer duration of regular use (12.8 vs. 8.4 years) by the time they enrolled in treatment. This finding matches results described by previous studies [18,25,35]. Even though age at onset was similar for the two genders, the male sample presented a greater length of opiate use than the female sample – a finding that could be attributed to sustained abstinence during pregnancy and a better level of compliance with treatment by female drug-dependent patients. Supporting this hypothesis, the women included in our sample had more children than the men. No gender differences were found to arise from the family/social relationships shown in the ASI composite score. The literature currently available has reported that males are more likely to meet the criteria set for another substance use disorder [16, 29, 31, 32, 33], while women were said to become more rapidly addicted to drugs such as cocaine and heroin [10]. Those results, however, were not confirmed by the present study. The assessment of comorbidity with the abuse of other drugs made it clear that men were more likely than women to meet the criteria for alcohol dependence (40.4% vs. 14.3%); this finding was correlated with the greater severity recorded in the ASI alcohol composite score [33]. On the other hand, women were found to be more likely to abuse or depend on

Table 3. Logistic regression: Relationship between sex and ASI composite score after adjusting for confounding variables 95% C.I. for EXP(B) B S.E: Wald df Sig. Exp (B) Lower Upper Years of regular use -0.074 0.036 4.1 1 0.042 0.9 0.9 1.0 Alcohol dependence -1.688 0.755 5.0 1 0.025 0.2 0.0 0.8 ASI Employment 1.47 0.633 5.4 1 0.020 4.4 1.3 15.1 ASI Alcohol -1.347 0.638 4.4 1 0.035 0.3 0.1 0.9 Constant 0.409 0.647 0.4 1 0.528 1.5 Dependent variable (gender): 0 ‘males’ 1 ’females’.

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sedatives, although that had not proved to be a significant factor in the reports published in the previous literature [9, 10, 16, 33]. 69.1% of the sample had a comorbid medical condition. Nevertheless, no differences appeared between female and male subjects in their previous medical conditions – a finding that is partly discordant with previous reports [3, 33, 25]. These discordant outcomes might be explained by the fact that studies display important differences in the recruiting setting. In the study conducted by Back et al, for example, the only patients included were those with a prescription opiate dependence comprising a previously diagnosed medical condition [2]. Moreover, Haugh et al evaluated the severity of addiction in a sample consisting mainly of HIV patients who were attending a methadone maintenance programme [19]. This study failed to detect any significant differences between genders as attested by the Medical ASI composite. It is worth noting that our centre is an integral part of a general hospital that offers patients a suitable follow-up of their organic diseases and easy coordination with the outpatient infectious disease programme. Significant gender differences in psychiatric comorbidity were revealed, with women being more likely than men to report a current and past history of psychiatric problems, as shown too in previous reports [9, 16, 20, 31]. Almost half (48.5%) of our female participants reported experiencing psychiatric problems in the past. This study also shows higher frequencies for Major Depression Disorders and Anxiety Disorders in treatment-seeking opioid-dependent women than in men (20.6% vs. 4.6% depression; 31.3% vs. 9.3 anxiety, respectively). Despite having found a significantly higher prevalence of psychiatric comorbidity in women, no statistically significant differences were found in the measurement of severity shown in the composite scores of the psychiatric status problem area, in contrast with the findings described by other authors [3, 10, 16, 20, 33]. A possible explanation for this result might be the tendency among female patients from our sample to seek treatment when they are in a more stable clinical phase, consistently with previous findings which report that women tend to enter treatment at an earlier stage of the course of their addiction, which is also generally viewed as a positive outcome factor [10]. Another possibility is that a bias in prioritizing the assessment of the drug abuse at the expense of comorbidity might have taken place. A further feasible explanation may be found in the intrinsic characteristics of the set of items used to assess the psychiatric status

problem area. The item “having depressive symptoms unrelated to substance abuse” is found to be difficult to assess without a maintained period of abstinence – a condition achieved in our sample. Another item is “receiving a pension for psychiatric disability”, and, as shown previously, no significant differences were found in the prevalence of psychotic disorders, which normally accounts for the impairment of disabled people, so increasing the likelihood that they will obtain a pension. In our study, the main differences were found in the prevalence of affective disorders that are rarely severe enough to make someone eligible for a disability pension. In the end, the item “being hospitalized in the past 30 days” is a finding that is limited in time and delimited in intensity; in other words, it does not necessarily reflect the presence of mental illness. In any case, this study did not detect more severe repercussions for women in the ASI psychological/psychiatric composite. In general, among treatment-seeking samples of individuals with substance use disorders drawn from a specific community, women consistently demonstrate higher rates of psychiatric comorbidities than men. It is thought that, in women, psychiatric illness may precede the development of substance use disorders, as postulated by the self-medication hypothesis, suggesting that women often use substances to cope with negative affect [11, 31, 33]. On the topic of axis II, the men in our sample showed a stronger tendency to have Antisocial Personality disorder (40% vs. 20%), in agreement with previous research [14, 16, 23, 24, 29, 31]. Despite this finding, the present study failed to detect any differences in the ASI legal status composite, as might have been expected, considering the close relationship between this disorder and legal problems. Another significant discovery was that no differences could be recognized in Borderline Personality disorder, in contrast to the study carried out by Grella in 2009 [16]. Even though the present study has observed a higher prevalence of cluster C Personality Disorder in the female sample, this finding should be interpreted with caution, considering the small size of the sample. Limitations The sample of patients examined may not be representative of the population of women and men seeking treatment for opiate dependence, as a large number of eligible subjects declined to participate. Moreover, we had no opportunity to compare our sample with those who did not participate. Further- 71 -


more, the small number of women showing some characteristics (for example, cluster C Personality Disorders) included in the study might not allow us to detect significant gender differences [4, 3, 21, 33]. In addition, even though the instrument used to evaluate severity was the European version of the ASI, some items might be not strictly comparable. For instance, there are descriptive variables, such as employment status, which are different for men and women, regardless of whether they have a substance use disorder (e.g., the high percentage of women who are housewives). 5.

Conclusions

Opiate dependence has been shown to determine a serious impairment in several areas of functioning. In our study, in line with previous research, women experienced more severe repercussions in the employment problem area than men. Men reported a greater severity in the ASI alcohol use composite score, which, in our sample, was correlated with a greater comorbidity with alcohol dependence. Women presented higher comorbidity with depression, even though these differences compared with men were not reflected by the psychiatric status composite score. Contrary to other outcomes, no differences in family/social relationships, legal status, medical status or drug use ASI composite scores were observed. These findings may prove to be useful for other outpatient drug programmes run by public health care systems in similar settings. Integrated treatments for opioid dependence and co-occurring psychiatric conditions are needed, as well as specific interventions (such as prevention of alcohol dependence in male patients) and systems of care that address collateral functional areas in the lives of women – for instance, working rehabilitation and other social services. By studying gender differences in terms of substance-related epidemiology, social factors and characteristics, biological responses, progressions to dependence, medical consequences, co-occurring psychiatric disorders, and barriers to treatment entry, retention, and completion can all be recognized as having a wide range of clinical, treatment, and research implications. References 1. Arfken C.L., Klein C., Di Menza S., Schuster C.R. (2001): Gender differences in problem severity at assessment and treatment retention. J Subst Abuse Treat 20: 53-57.

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Martinez Luna N., Eiroa-Orosa F.J., Casas M. (2011): Therapeutic management and comorbidities in opiatedependent patients undergoing a replacement therapy programme in Spain: the PROTEUS study. Heroin Addict Relat Clin Probl 13(3): 5-16. 29. Rowan-Szal G.A., Chatham L.R., Simpson D.D. (2000): Importance of identifying cocaine and alcohol dependent clients. Am J Addict 9(1):38-50. 30. Shand F.L., Degenhardt L., Slade T., Nelson E. (2011): Sex differences amongst dependent heroin users: Histories, clinical characteristics and predictors of other substance dependence. Addict Behav 36(1-2):27-36. 31. Shu-Chuan C., Hung-Yu C., Yuan-Ying C. (2007): Psychiatric comorbidity and gender difference among treatment-seeking heroin abusers in Taiwan. Psychiatry and Clinical Neurosciences 61, 105-111. 32. Tetrault J.M., Desai R.A., Becker W.C., Fiellin D.A., Concato J., Sullivan L.E. (2007): Gender and non medical use of prescription opioids: results from a national US survey. Addiction 103, 258-268. 33. Tremeau F., Darreye A., Khidichian F., Weibel H., Kempf M. (2002): Impact dún traitement de substitution par methadone sur des sujets dependants aux opiacés évalué par lÁddiction Severity Index et des contrôles urinaires. LÉncéphale 28:448-53. 34. Tuchman E. (2010): Women and addiction: the importance of gender issues in substance abuse research. J Addict Dis 29(2):127-38. 35. White K.A., Brady K.T., Sonne S. (1996): Gender differences in patterns of cocaine use. Am J Addict 5; 259-261. Acknowledgments We are grateful to our research team for their support, particularly our Psychologist Research team: Susana Gómez-Baeza, Sonia Fuentes and Yasmina Pallarés. Special thanks are due to Sergi Valero for his methodological assistance. Role of the funding source Grant of the Departament de Salut, Government of Catalonia, Spain, for publication. Contributors All authors revised and approved the final form of the manuscript. Conflict of interest The authors have no potential conflicts of interests to declare.

Received January 6, 2014 - Accepted April 4, 2014 - 73 -

Regular article Heroin Addict Relat Clin Probl 20xx; xx(x): xx-xx

Limbic system irritability and drug dreams in heroin-addicted patients Claudio Colace 1, Sergio Belsanti 2, and Antonia Antermite 3 1 U.O.C. Psychology, AUSL Viterbo, Civita Castellana, Italy, EU 2 Centre for Drug Addiction, AUSL Viterbo, Tarquinia, Italy, EU 3 U.O.C. Psychology, AUSL Viterbo, Viterbo, Italy, EU

Summary Background. Drug dreams, that is, the dreams of drug-addicted patients with contents related to their craving for the drugs they are addicted to, have been investigated to determine their clinical and prognostic significance, as well as for their implications from the standpoint of general dream research and theory. Recent progress in the neurobiology of drug addiction and drug craving, affective neuroscience, and the neuropsychology of dreaming, provide a background for investigating the possible neurobiological correlates of these dreams, which may deepen our understanding of the close link between drug dreams and the craving for drugs. Aim. This paper investigates the relationship between drug dreams and limbic system activity in drug-addicted patients as measured by means of the Limbic System Check List-33 (LSCL). Methods. 53 heroin-addicted subjects were interviewed about their drug dreams; the interviews made use of the Drug Dreams Questionnaire. Results. The results show that drug-addicted patients reported an LSCL mean score that indicates limbic system irritability. Furthermore, patients whose experience included drug dreams reported a higher, statistically significant LSCL mean score than patients who had not had any drug dreams. Our results are also consistent with previous studies regarding the phenomenological picture of drug dreams and their clinical applications. Discussion and conclusion. We assume that, in the patients who reported drug dreams, the higher LSCL scores may be due to the presence of a stronger drug craving, of which the higher mesolimbic-mesocortical dopamine tone is the neurobiological correlate. The association between the greater limbic DA tone and the occurrence of drug dreams appears to be consistent with the results of clinical-anatomical studies on dreaming with reference to the crucial role of the mesolimbic-mesocortical dopamine system in the instigation of dreams. Key Words: drug dreams; addiction; limbic system; seeking system.

1.

Introduction

‘Drug dreams’ is the term commonly used in the literature to define the dreams of drug-addicted patients that have contents related to their craving for the drugs they are addicted to [10, 12, 15, 21, 36, 56, 59]. These dreams are a well-documented clinical phenomenon in all forms of addiction [10, 18, 19, 36, 49, 59] and have been investigated in terms of clinical usefulness and prognostic significance in the treatment of addicted patients [4, 10, 12, 29, 36, 46, 57, 59, 65, 72], as well as in their implications from the standpoint of general dream research and theory [15, 18, 28, 14, 16, 42, 45]. More recent studies have also made an attempt to investigate the possible neurobiological substrate

of drug dreams [17, 19, 42] by integrating current knowledge of the neurobiological substrate of drug addiction [54], the findings of what is now known as “affective neuroscience” [55, 71], and the results of clinical-anatomical studies of dreaming [61, 62, 73]. Studies on the neurobiology of addiction converge in indicating the mesolimbic-mesocortical dopaminergic (ML-MC DA) system as the principal area engaged in addiction diseases [9, 55, 64]. This system arises in the mid-brain ventral tegmental area (VTA) and is projected towards the limbic structures – in particular, the nucleus accumbens (NAc), the amygdala (and the so-called “extended amygdala”), the hippocampus, the prefrontal cortex, including the orbitofrontal portion (OFC) and the cingulate gyrus [20, 24, 25, 33, 47, 48]. According to the “incentive-

Corresponding author: Claudio Colace, Ph.D., via Luigi Volpicelli, 8, 0133 Roma, Italy, EU Phone: 3336148977; e-mail: [email protected]

75

Heroin Addiction and Related Clinical Problems xx(x): xx-xx

sensitization” model of drug addiction [60], repeated exposure to addictive drugs produces a long-lasting sensitization in the ML-MC DA system that normally regulates the attribution of incentive salience to stimuli, so that an abnormal level of incentive salience comes to be attributed to drugs and drug-associated stimuli, which, as a result, become pathologically amplified (so leading to “abnormal wanting”, and a craving for drugs). The ML-MC DA system has also been described in “affective neuroscience” studies as the core component of the “SEEKING” system [38, 55] or “wanting” systems [5,6], that is, the neuronal circuits involved in the instigation of goal-seeking behaviours and appetitive interactions with the world, including hunger and sexual desire (i.e., the basic drives), which comprise the craving for drugs experienced by people who have become drug-addicted. According to Solms’s clinical-anatomical studies, the part of the brain involved as the “primary generator” of dreaming is the white matter surrounding the frontal horn of the lateral ventricles (i.e., the ventromesial quadrant of the frontal lobes), exactly the part of brain that includes the ML-MC DA system [61, 62]. Actually, Solms found an overall cessation of dreaming in a group of patients affected by bilateral frontal lobe lesion [61]. This finding was later confirmed by Yu [73]. Johnson [42 43, 44], in the first attempt made to integrate the above evidence, suggests that drug dreams arise from an alteration of normal dreaming processes (drug dreams do not occur in healthy people) caused by persistent changes in the neurological functions of drug-addicted patients (i.e., the upregulation of the ML MC DA system). Subsequently, Colace [17] and Colace et al. [19], in agreement with Johnson’s hypothesis, found that a sample of drugaddicted patients showed limbic system irritability, as measured by means of the Limbic System Check List-33 (LSCL-33) [68], and a high frequency of drug dreams, while occasional drug users (i.e., those with no diagnosis of drug dependence, and without any presence of drug craving) did not report either limbic irritability or drug dreams. These authors hypothesized that the limbic system irritability of drugaddicted subjects, as the expression of the upregulation of ML-MC DA circuits, could be the signal of a greater availability of dopaminergic tone that, in its turn, could be the specific neurobiological background in which drug dreams might preferentially occur [19]. Actually, there is evidence that: a) drugaddicted patients show a limbic system irritability [7, - 76 -

39, 67] which is positively correlated with alcohol craving [7, 39], and that: b) drug dreams are more frequent when there is an increase in drug craving [3, 12, 28] that is neurobiologically mediated by greater ML-MC DA release levels [23, 24, 26, 69]. Investigation of the neurobiological substrate that underpins drug dreams could have a useful impact on our understanding of the close link between drug craving and these dreams; this, in its turn, could lead to a better clinical and prognostic use of these dreams, and to their use in evaluating the effectiveness of the pharmacological treatment of drug addiction. The study of Colace et al. [19] was the only one in which drug-addicted patients were scrutinized both in terms of their recollections of drug dreams and of the measurement, even if indirect, of limbic system activity, and was not followed by any attempt at replication. Furthermore, the hypothesis about the role that high dopamine levels might have in the onset of drug dreams still calls for some more direct testing. The twin aims of this study were to evaluate limbic system activity in heroin-addicted patients, and compare the degree of limbic system activity between drug addicts who reported drug dreams and those who did not. We formulate two main hypotheses: (a) drugaddicted patients all show high LSCL-33 scores, so suggesting limbic irritability; (b) the drug-addicted patients who report having had drug dreams actually record LSCL scores that are higher than than those of drug-addicted patients who do not report that kind of event. The questionnaire on drug dreams used in the present study also allowed us to investigate the following topics: 1) frequency of drug dreams, 2) when drug dreams appear (i.e., abstinence vs. regular use), 3) contents and emotions in drug dreams and on awakening, 4) the role of drug dreams in making abstinence more likely on the next day, 5) the influence of pharmacological treatment for drug addiction on the occurrence of drug dreams. 2.

Methods

2.1 Subjects There were 53 drug-addicted subjects (45 male, 8 female), mean age 34, who arrived consecutively at the Centre for Drug Addiction over a six-month period. Their drug dependence diagnosis was based on DSM IV criteria (2). All subjects used heroin as their primary drug of dependence. Of these subjects, 8 were also dependent on cocaine, 2 on alcohol, and

C. Colace et al.: Limbic system irritability and drug dreams in heroin-addicted patients

2 on cannabis. Of these subjects, 50 were pharmacologically treated. Forty-four (88%) of them were treated with methadone, six (12%) with buprenorphine. The remaining three subjects were treated with psychological support only.

2.4 Ethical standards

2.2 Assessments

Analyses were performed using the Statistical Package for Social Science (SPSS) for Windows, Version 11.0. Frequencies, percentages, means, median, binomial test and t-test were the statistical indicators used.

The data on drug dreams were collected through a Drug Dreams Questionnaire (DDQ) that included questions about drug dreams since the start of heroin dependence and the latest drug dream recalled (Appendix 1). Limbic system activity was assessed by means of the Limbic System Checklist, LSCL-33 [68]. LSCL is a 33-item self-report questionnaire designed to measure temporo-limbic activity. This questionnaire was originally devised to ascertain the frequency symptoms suggestive of temporal lobe epilepsy. Subjects with well-documented temporal lobe epilepsy that was responsive to anticonvulsants reported high scores. The questionnaire included four item areas: somatic, sensory, behavioural and memory symptoms suggestive of limbic system dysfunction. The LSCL33 showed good psychometric properties and internal consistency (Cronbach’s alpha 0.90). Subjects rated the frequency of symptoms using a 4-point Likert scale (never=0, rarely=1, sometimes=2, often=4). The subjects who had temporal lobe epilepsy reported high scores (range 23-60), while normal adults reported scores <10. The LSCL-33 is correlated with other measures of limbic dysfunction (e.g., the Hopkins Symptom Checklist) [45]; and the CPSI (Complex Partial Seizure-like) [67]. The following information was noted for each subject: type of pharmacological therapy (buprenorphine, methadone, psychological support only), dosage (mg/day) related to the time when the patient had the latest drug dream, and other possible forms of secondary drug dependence (Appendix 1). 2.3 Procedures The data were collected in two Centres for Drug Addiction. The interviewers, who were not aware of the research aims, after obtaining the patients’ informed consent, asked each one of them to answer the DDQ questionnaire and the LSCL-33.

The study was carried out according to the principles laid down in the Helsinki Declaration. 2.5 Statistical analyses

3.

Results

Two subjects did not complete the LSCL-33. LSCL-33 mean score in drug addicted subjects was 23.29. Drug-addicted patients who reported drug dreams had significantly higher LSCL-33 scores (mean = 26.59) than the other patients (mean = 16.71) (T-test = -2.214, df = 47.525, p = .03) The patients recalled two (general) dreams a week (median score). There were 35 patients (66% of the group) who reported having had drug dreams since they started using heroin; the remaining 18 (34%) did not report having had any drug dreams. Almost half of the patients had drug dreams while not using heroin (45.7%) (Table 1). Very few patients had drug dreams during a period of regular drug use (8%). Table 1. When drug dreams occur Occurrence of drug dreams When I decided to stop using heroin When I could no longer use heroin When I was using heroin Either (both during use and non-use) Uncertain

N 9 7 3 15 1

% 25.7 20.0 8.5 42.8 2.8

Among the patients who recalled their most recent drug dreams, 53% had not used heroin for at least a week previously, while 47% had used it. Drug dreams were reported even after a long period of abstinence (six months or more), but they mostly occurred (56%) after abstinence from drug use lasting for a period of 15 days to 3 months (Table 2). Of the patients interviewed, ten had been in a community (without any opportunity to use drugs) in previous periods. Of these ten, five (50%) reported having had drug dreams while they were staying in a - 77 -


Table 2. Duration of abstinence before onset of drug dreaming Abstinence N % 15 days 3 16.7 At least 1 month 4 22.2 About 3 months 3 16.7 About 6 months 2 11.1 More than 6 months 6 33.3 N=18 (17 patients were unable to answer this question)

Table 3. Type of dream about drugs Type of dream about drugs Seeking (buying, seeing, having) my drug Using the drug Unsuccessful attempt to use heroin Seeing others use heroin Fear of being caught Refusing heroin

N

%

15

23.0

7 13 4 3 0

20.0 37.1 11.4 8.6 0

therapeutic community. The dream contents are shown in table 3. The most frequent type of drug dream comprised those that were about “seeking or using heroin” (43%). This category was created by putting together the answers of patients who used heroin in their dreams with other responses in which patients sought, bought, saw, or took heroin in the dream (i.e., activities related to drug Table 4. Emotions in the most recent drug dream and on waking up Emotions felt in dream N % Anguish 15 42.9 Pleasure 6 17.1 Guilt 3 8.6 Fear 3 8.6 Anger 1 2.9 Other emotions 3 8.6 Do not recall 4 11.4 Emotion felt on waking up Anger at realizing that I had not really 7 22.6 used heroin Relief, on realizing that I had not real4 12.9 ly used heroin I felt no emotion 6 19.4 I felt other emotions 4 12.9 I felt anguished 3 9.7 I felt satisfied 3 9.7 I felt irritated by the idea of having 4 12.9 dreamt about heroin No answer 4 11.4

- 78 -

use). The second category of drug dreams was about “unsuccessfully attempting to use heroin”. In these dreams, the attempt to use heroin failed for some reason. No dreams of drug refusal were observed. The drug that appeared in the dreams was the one that subject was dependent on. The majority of dreamers reported feelings of anguish in their drug dreams, and then a feeling of anger and disappointment on waking up because they had not really taken heroin. Other emotions during the dreams and on waking up are shown in table 4. Most patients who had drug dreams did not use heroin on the next day (71.8%, 23/32), while the remaining patients (28.2%) used heroin (binomial test, p = .022 based on Z approximation). The patients who stayed clean felt a lower perceived drug craving (26%, 6/17) on waking up, while the others experienced no change (73.9%). Of the patients who used heroin on the next day, 33% (3/9) felt a greater drug craving, while 66% did not. At the time of reported drug dreams, 25 out of 34 patients were receiving methadone treatment, 4 were being treated with buprenorphine (mean: 15 mg/ day, range 2-25 mg/day), and 5 were not receiving any pharmacological treatment. Of the patients being treated with methadone, 14 were on a low, anti-withdrawal dosage (50 mg/day) and 10 were on a high, anti-craving dosage (70 mg/ day or more): drug dreams occurred in a similar way in patients in these two situations. 4.

Discussion

4.1. When drug dreams are likely to appear Almost one out of two patients reported having had drug dreams during periods of drug unavailability, while only three patients stated explicitly that they had had drug dreams while using drugs regularly. A substantial number of patients, probably due to the difficulty they experienced in remembering in which condition – abstinence or regular use – they had had drug dreams, responded ambiguously: "in both conditions”. The first result is consistent with patients who had spent time in a therapeutic community, without any opportunity to use drugs; the proportion of these patients who reported having had drug dreams was one out of two. Focusing now on the last drug dream remembered, as a qualitative observation (without statistical significance) it should be noted that more than half of the patients reported that they had not used drugs


at least during the preceding week, and that they had remained abstinent during the three months preceding the most recent drug dream. Among the patients who reported having used drugs during the week preceding the drug dream, the answers collected did not allow us to understand whether such use referred to daily, continuous use, or to a single relapse after a period of abstinence. In the latter case, the relapse itself may have been preceded by a sudden recrudescence of drug craving, as indicated, in fact, by the onset of drug dreaming. The above data are in line with previous studies that had found that the onset of drug dreaming is triggered by a condition of abstinence (10, 13, 15). For example, previous observations have shown that during imprisonment or after admission to hospital, in fact, whenever these patients find difficulty in obtaining drugs – for example, due to lack of money or due to being detained by the police – they report drug dreams [13, 15, 17, 49, 72]. Similarly, previous studies show the presence of drug dreams in the initial stage of abstinence from drug use, that is, from one or two weeks to two or three months counting from the start of treatment of drug-addicted patients [10, 18, 36, 57]. It is very likely that the increased frequency of drug dreams in a condition of abstinence is due to the frustration arising from drug craving (i.e., an increase in drug craving pressure) that patients experience in this circumstance. Indeed, some authors have suggested that abstinence produces a motivational state resembling a biological deprivation (e.g., hunger), and increases the motivational impact of drugassociated cues, multiplying craving intensity through a greater presence of acute drug craving episodes [24, 27, 47, 51, 66]. In any case, when drug craving is, in itself, already at a high level (without being exacerbated by abstinence), or when it suddenly becomes recrudescent, this may result in a return and/or increase in the occurrence of drug dreams [18]. 4.2. Phenomenological aspects of drug dreams Our data confirm that drug dreams are a widespread phenomenon among drug-addicted patients. Indeed, even if our patients were generally not “good” dream recallers, they reported drug dreams in a high percentage of cases, as found in previous studies with heroin-addicted patients and with patients with other forms of dependence [4, 12, 18, 37, 59]. Most studies agree on the fact that the most frequent content of drug dreams is the use of the drug the patient is addicted to (i.e., the patient finds him- or herself us-

ing that particular drug) and other activities related to drug use, that is, seeing/seeking drugs, handling or buying drugs/alcohol. Another frequent content is an “unsuccessful attempt to use drugs” [10, 12, 13, 15, 19, 37, 49, 59, 72]. Drug dreams presenting an explicit rejection of the drug have been observed more rarely [4, 59]. Our results confirm this phenomenological picture. The common theme of drug dreams in our patients is their craving for drugs that they attempt to satisfy, sometimes successfully, sometimes not. As noted in other studies, in these dreams there may also be no more than the pleasant possession of a drug, a feature that may forerun or partly predict its use (18). The main emotions in drug dreams were “anguish” and “pleasure”. The reasons for these emotions are quite clear. In drug dreams there may be the pleasure of using, or attempting to use drugs, without the presence of anguish when the desire for the drug seems to be consciously accepted by the dreamer. These types of drug dreams have been interpreted, in psychoanalytic terms (31), as an “infantile” form of wish-fulfilment dreams in adults [10, 13, 15, 18, 50]. For drug dreams as assessed from a psychoanalytic viewpoint, see also: [22, 28, 58]. On the other hand, when the desire for a drug is rejected by the dreamer’s conscience (i.e., when the drug is the aim of a repressed wish), and then its satisfaction or attempted satisfaction in the dream clashes with the patient’s new intention to change (i.e., stay clean, refrain from using heroin), feelings of anguish and sometimes guilt may occur. As found in previous studies, drug dreams were followed, on awakening, by two main feelings – in particular, anger on realizing that drug use was not real, or, by contrast, relief on realizing that the relapse was not real [8, 15, 30]. Colace [15] observed that the feeling of relief is usually associated with dreams about drug use, while anger, on waking up, may be associated with drug dreams about an unsuccessful attempt to use a drug. The data collected here are not numerically sufficient to determine whether these different feelings match the different types of dreams (e.g. evoking the use of a drug, or else a failed attempt to use it). 4.3. Limbic system irritability and drug dreams The present study confirms previous indications of high LSCL-33 scores among drug-addict patients (research hypothesis a). The LSCL mean score shown by our patients was similar to the scores obtained in previous studies by heroin-addicted patients [17, 19] - 79 -


and by alcoholic patients [7, 39], and it suggests limbic irritability. The LSCL mean score obtained by drug-addicted patients is considerably higher than the score obtained by normal subjects and sporadic drug abusers (i.e., those not meeting the criteria for a diagnosis of drug dependence) (< 10) [1, 19]. It is therefore plausible to interpret the limbic irritability of drug-addicted patients as the expression of MLMC DA pathway upregulation caused by prolonged drug exposure [60]. The present study shows that patients who reported drug dreams had higher LSCL scores than those who did not (research hypothesis b). We now hypothesize that, in the patients who reported drug dreams, the higher LSCL scores may be due to the presence of a stronger and more persistent drug craving, of which the higher ML MC dopamine tone is the neurobiological correlate. A positive relationship between drug craving, and drug dream onset and frequency has, in fact, been found repeatedly [3, 10, 11, 15, 18, 28, 57], together with an increase in ML MC dopamine release when drug-addicted patients experienced a strong desire for drugs (i.e. drug craving), as shown in functional neuroimaging studies (34, 35, 69, 70). In any case, LSCL-33 scores have been found to be correlated with alcohol craving and with substance abuse among college students [1, 7, 39]. From the point of view of general dream research and theory, the association between a more intense limbic DA tone and the occurrence of drug dreams appears to be consistent with the results of clinical-anatomical studies on dreaming, as regards the crucial role of ML MC DA triggering the dream [61, 62, 73]. In fact, according to Solms, the part of the brain that is involved as the “primary generator” of dreaming is the white matter surrounding the frontal horn of the lateral ventricles (i.e., the ventromesial quadrant of the frontal lobes), that is, the part of the brain which includes the mesolimbic–mesocortical dopamine pathways (ML–MC DA) that arise from the cell group of the ventral tegmental area, and extend towards the limbic and frontal structures. The ML–MC DA pathways are also described in affective neuroscience as the core of the ‘seeking’ system – the instigator of goal-seeking behaviour and of appetitive interactions with the world, the system that houses the basic drives (hunger, sexual desire, etc.) [55]. Now the seeking system also houses the new drive in drug-addicted subjects, that is, the craving for drugs, with the possibility, which is exclusive to these subjects, of triggering dreams linked to this drive (i.e., drug dreams). - 80 -

Colace [16] and Colace et al. [19] in their “dopaminergic model” of drug dreams, assumed that the onset of drug dreaming might be favoured, in abstinent conditions (i.e., drug craving intensification), by the fact that the non-use of drugs hinders the “discharge” at a higher level of drug craving/ DA release. In other words, in a condition of an already upregulated ML–MC DA system, at a moment of high vulnerability to drug-conditioned cues, due to abstinence from drugs, the onset of drug dreaming should be instigated by a temporary increase in DA release that has not yet been ‘discharged’. Conversely, during regular (daily) use of drug, when the increased level of drug craving / dopamine release are continually discharged, zeroed and the baseline DA levels are re-established (i.e., drug craving satisfaction), drug dreams should not appear, or should appear less frequently. In the light of the data reported here, we may suppose that the dopaminergic onset of drug dreaming has a higher probability of being implemented in those subjects who are already experiencing limbic system irritability and a greater availability of dopamine. 4.4. Drug dreams and maintenance of abstinence upon awakening Most of our patients who had had drug dreams did not use heroin on the next day. This is consistent with other studies that have shown that drug dreams increase a patient’s probability of staying abstinent from drugs [10, 36, 46, 50, 57)]. Many authors have suggested that one function of drug dreams is to offer the dreamer a “safe way” [3, 10, 13, 15, 22, 46, 53, 58] and have pointed out that drug dreams (or drinking dreams) may help the dreamer to develop strategies for coping with drug craving and staying sober/ clean, [32, 53, 57, 63]. Indeed, drug dreams seem to enable a ‘safety-valve’ type of compensation, at a hallucinatory level, of the continuous urge to use drugs (‘drug craving’). In this sense, their function is to “discharge” the pressure of drug craving. In parallel with this, Choi [10] observed that alcoholics who reported "drinking dreams" had been tolerating better, and for longer periods, their craving for alcohol than alcoholic patients who did not have such dreams. Providing an alternative view, some authors suggest that drug dreams serve as reminders of the adverse consequences of drug use or of drinking, or as reminders of the advantages of staying clean. These dreams help patients to prevent relapses [10, 36, 40]. In particular, Hajek and Belcher [36], in their "aver-


sive conditioning theory", assumed that drug dreams, because of their emotionally negative impact on the dreamer (i.e., by inducing panic and/or guilt), probably reduce the chances of repeated drug use. From this point of view, Hajek and Belcher [36] proposed attaching more importance to these dreams in therapy (e.g., by promoting their recollection by these patients and focusing patients’ attention on their contents). In a smaller number of cases, we found that patients had relapses after their drug dreams. This effect has also been observed in the existing literature. In this case, drug dreams may even have a function that stands in opposition to “discharge”, that is, a function of providing an incentive for drug craving [27, 52]. For example, Christo and Franey [12] observed that some polydrug users who had experienced relapses claimed that the presence of drug dreams had contributed to those relapses. According to these authors, there is the possibility that drug dreams constitute vivid memory recall cues that may induce drug craving. This same effect was also found in some tobacco smokers [57]. It has been hypothesized that this incentive effect on drug craving should be particularly pertinent to those drug dreams that were not entirely gratifying, or in which the use of drugs failed or was interrupted by the dreamer waking up [15]. These drug dreams can trigger drug craving upon awakening and during the following days. By failing to fulfil drug craving, these dreams eventually turn it on. They act as a sort of appetizer before a meal that is not eaten, leaving the dreamer even hungrier than before. Here we can distinguish at least two cases: a) drug craving is heightened in the post-dream state of being awake because the dream has failed (fully or partially) in its “discharge” action, or b) the dream in itself acts as a drug-related appetitive cue for craving [15, 18]. The quality of the data collected (i.e., the non-availability of the written text of the dream) has prevented a further classification of dreams with respect to remaining abstinent on waking up, so, at present, the hypothesis that prolonged abstinence may be associated with dreams that represent particularly gratifying results, and, conversely, that the increased risk of relapse may be associated with dreams that, by failing to satisfy the craving, end up by stimulating it, cannot be confirmed. At a purely descriptive level, however, we can report our finding that, in those who had relapses on the following day, the dreams centred on drug issues dealing mainly with the non-use of heroin, and, conversely, in those who were experiencing a prolonged abstinence, the themes of their drug dreams were mostly about buying, having, seeing,

looking at and using heroin (i.e. themes that were all emotionally rewarding). It should be noted that in both cases, i.e. situations of prolonged abstinence or of relapse, this rarely corresponds to a decrease or to an increase, respectively, in the craving perceived by the subject. The conscious desire to use the substance is not always indicative of an unconscious craving that may increase or decrease the risk of a relapse. 4.5. Drug dreams and pharmacological treatment for addiction We know that the goal of pharmacological treatment in drug addiction is to mitigate the adverse withdrawal symptoms and reduce the craving for drugs. The agonist pharmacological treatments, such as methadone for opiates, act mainly on the ‘phobic aspect’ of craving, that is, the need to avoid withdrawal symptoms, whereas antagonist treatments, such as naltrexone for opiates, and, to some extent, buprenorphine too, take effect by barring any opportunity to experience the pleasant effect of drugs (i.e., they exert an “anti-craving” action), in the attempt to fight the very desire for drugs (i.e. the “appetitive” aspect of craving). In our patients the presence of drug dreams does not seem to have been influenced by the type of pharmacological therapy or by its consequences on various aspects of drug craving. According to the previous literature [13, 15, 18, 19], it has been shown that drug dreams occur in heroin-addicted patients who take a low, antiwithdrawal methadone dosage, but also in those who take a high, anticraving methadone dosage, and again by those who take buprenorphine, which has a mixed action as a µ-opioid partial agonist/k-opioid partial antagonist. Thus, pharmacological action, whether directed against ‘phobic craving’ or against ‘appetitive craving’, can attenuate a strong drug craving, so much so that it continues to occur regularly in dreams. The fact that drug dreams are present in people undergoing therapies that act on different aspects of craving suggests that these pharmacological treatments do not always succeed in reducing drug craving. Its extraordinary strength, far from being tamed, is ready to trigger drug dreams. The study of drug dream frequencies in patients receiving various types of pharmacological treatment that act on different aspects of drug craving is likely to contribute to a better understanding of drug craving itself. These results are also consistent with studies on the drug dreams of alcoholics and tobacco addicts. - 81 -


Hajek and Belcher [36] observed that smoking-related dreams appear in abstinent tobacco-addicted subjects who receive pharmacological treatment with nicotine chewing-gum to mitigate most withdrawal symptoms, and they concluded that these dreams appeared to be generated primarily by cognitive processes of craving, rather than directly by falling blood nicotine levels. Choi [10] noted too the presence of drinking dreams among patients who were taking disulfiram, an aversive treatment for alcohol that causes an unpleasant reaction when alcohol is consumed. In his study, although the alcoholics who were being treated with disulfiram could remain abstinent for a greater number of days than those who did not take disulfiram (so allowing a better control over drug craving), they continued to report drug dreams. 5.

Conclusions

Drug dreams are a widespread phenomenon among drug-addicted patients. In this study we have confirmed the phenomenological picture of these dreams and their potential clinical applications, especially as a “window” function on the degree of drug craving and the evolution of drug-addicted patients. The onset of drug dreaming is related to the presence of drug craving, which is the result of an upregulation of the ML MC dopaminergic system; this, in its turn, as suggested by this study, is revealed by limbic system irritability in all these patients, but is more marked in those who have drug dreams. We interpret limbic system irritability (which is directly mirrored in an increased availability of ML MC dopamine), as the neurobiological background condition in which, especially during abstinence from drugs – a condition known to show a greater propensity to acute drug craving episodes and higher DA release levels – drug dreams are more likely to appear. Further studies are now needed to investigate this neurobiological background of drug dreams, which might deepen our understanding of the close connection between drug dreams and the craving for drugs. In terms of general dream research and theory, drug dreams are found to be particularly revealing in showing the dopaminergic activation of dreaming and the key role of the brain areas involved in the basic motivations that induce the dreaming process.

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APPENDIX 1. DRUG DREAMS QUESTIONNAIRE

We are collecting information on the dreams of our patients. Please answer the following questions by placing a cross in the squares. Every answer that you give is strictly confidential. Thanks for your cooperation. Date _________ Age_________ Sex___________ How many dreams do you usually recall in a week? 0 1 2 3 4 5 6 7 8 9 10 Did you have dreams about heroin right from the start of your use of this drug?] ! Yes

! No

Usually, when you have these dreams about heroin? ! When I use heroin ! When I cannot use heroin (e.g., when I do not have the money to buy it) ! During periods when I decide to stop using heroin ! Both when I use heroin and when I do not use heroin ABOUT YOUR MOST RECENT DREAM ABOUT HEROIN, ANSWER THE FOLLOWING QUESTIONS:

When did you have this dream?: ______________________ In my dream: ! I used heroin ! I was trying to use heroin, but I could not ! I saw others who were using heroin ! I refused to use heroin ! Other: __________________ (If possible, mark the date or period) ____ In your dream, what did you feel?: ! Fear

! Pleasure

! Anguish

! Anger

! Guilt

! Other _____! Don’t know On waking up from your dream, did you feel?: ! Disappointed, because I understood that I had not really had any heroin ! Reassured, because I understood that I had not really made use of heroin ! Normal, without any particular emotion ! Other ________________________________ On waking up, was your desire to use heroin: ! Unchanged ! Increased ! Decreased

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The day after that dream, did you use heroin?

! Yes

In the week prior to this dream, did you use heroin? ! Yes

! No ! No

If you have answered “No”, indicate how much time had passed since you last used heroin before having this dream: ! 15 days

! At least 1 month

! About 3 months

! About 6 months

! ______ months

(Only for users who have been in a Therapeutic Community) Do you remember having had dreams about heroin when entered your therapeutic community? !Yes ! No To be completed by the Drug Addiction Unit operator Drug therapy taken by the patient (NB: when the patient's dream about heroin indicated therapy in the period in which he recalled the dream): Buprenorphine mg.__________Methadone mg._______ Presence of secondary dependences: ! Cocaine ! Alcohol ! Cannabis ! Other

Received February 22, 2014 - Accepted July 5, 2014 - 86 -


Induction and switch to buprenorphine-naloxone in opioid dependence treatment: Predictive value of the first four weeks Sabine M. Apelt 1,2, Norbert Scherbaum 3, and Michael Soyka 2,4 1 Certum Consulting – Scientific Research, Ruhpolding, Germany, EU 2 Ludwig Maximilian University, Munich, Germany, EU 3 LVR-Hospital Essen, University Duisburg-Essen, Germany, EU 4 Private Hospital Meiringen, Meiringen, Switzerland

Summary Background: Clinical studies report the highest risk of dropout in the first few weeks of opioid dependence treatment. This secondary analysis of data from a non-interventional study with buprenorphine-naloxone (BNX) aims to evaluate the predictive value of the treatment outcomes after the first four weeks in routine care. Methods: Data collected from 69 sites in Germany, came from a multicentre 12-month study involving 337 opioid-dependent patients. Results: Patients with negative urine screenings for opiates, cocaine or benzodiazepines at screening, a maximum daily dose of 8mg BNX during the first four weeks, significantly lower Global Severity Index (GSI) on the SCL-90-R at day 0 and again at week 4, had a significantly higher chance of being retained in treatment. The patients who switched from d/l-methadone, levo-methadone, buprenorphine or active heroin use showed differences in almost all the parameters that were evaluated. Conclusion: The first four weeks of treatment with BNX have a high predictive value for the treatment outcome, especially in terms of urine screening, dosing of BNX and psychiatric distress. But the physician in charge needs to determine if the patient has been pre-treated with d/l-methadone, levo-methadone or buprenorphine, or whether the patient is inducted to BNX directly from heroin, because most of the predictive values seem to be unique for a subgroup of patients only. Key Words: buprenorphine-naloxone, opioid dependence treatment, predictors of treatment outcome, first weeks of treatment

1.

Introduction

Drug dependence therapy with maintenance drugs is an established method for the reduction of criminal behaviour and somatic disorders, including infectious diseases and drug-related deaths, while improving the somatic, mental and social well-being of drug-dependent users [10, 21, 26, 27,28, 32,]. The first goal of maintenance treatment is to stabilize the patient with an adequate dose of the maintenance drug, to prevent withdrawal symptoms, and risky and health-damaging behaviour. An improved status of this kind will give a drug-dependent patient an opportunity to regain control over his/her life [8, 10]. The first four weeks of treatment seem to be

extremely important for the general course of opioid dependence treatment. Some clinical studies report the highest risk of dropout and relapse in the first week of opioid dependence treatment [20, 30]. But the longer a patient stays in maintenance treatment, the higher the chances are of accomplishing positive treatment outcomes, including complete abstinence from illicit drug use [11, 23, 24, 30]. To keep the patient in treatment is one of the major challenges of maintenance therapy [6], and is influenced by many factors. Adequate dosing seems to play a major role. Buprenorphine doses of 8 mg/day or less resulted in lower retention rates [12] and higher numbers of positive opioid urine screenings [3]; by contrast, higher doses (12-16mg) resulted in higher chances of

Corresponding author: Sabine M. Apelt, Dipl.-Psych, Certum Consulting – Scientific Research, Ort 1, D-83324 Ruhpolding, Germany, EU & Ph.D. student at Ludwig Maximilian University, Nussbaumstr. 7, D-80336 Munich, Germany, EU E-mail: [email protected]

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achieving complete abstinence from opioid drug use [7, 18, 19, 22,]. Thus, an adequate dose of buprenorphine-naloxone is a crucial factor in keeping drugdependent patients in treatment. Other predictive variables for high retention and positive treatment outcomes are being older, having a job, having a history of treatment, being cocainefree at baseline [1, 4, 15, 23, 24, 30], and having cocaine- and heroin-free urine screenings in the first few weeks of treatment [9]. Predictors of negative treatment outcomes include cocaine use and polydrug use at baseline and during treatment [6, 9, 20, 25, 30]. Opioid-dependent drug users show extreme heterogeneity in many of their characteristics [32]. In any case, it can be assumed that, especially in the early phases of treatment, certain characteristics and variables are unique to each patient, and can be used as reliable signals of a positive or negative course and outcome of opioid dependence treatment. These signals, if recognized at an early stage of treatment, could be used to sdjust the treatment plan, and help the patient to be retained and/or reach the ultimate objective of complete abstinence. Despite several clinical trials with tight assessment schedules for the early weeks of treatment [14, 16, 31], there have been no published multisite, longterm, observational, non-interventional studies in routine care that provide a detailed description of the first four weeks of treatment with buprenorphine-naloxone (BNX), and allow an assessment of the reliability of predictors for positive treatment outcome. Only one single-site, observational cohort study by Stein et al. [30] described the results of 41 opioid-dependent patients treated with buprenorphine-naloxone, with a follow-up of 6 months; their results on retention and its predictive factors reflected those found in clinical trials [30]. This secondary analysis of data from a nationwide, non-interventional, observational study with buprenorphine-naloxone in routine care [2] aims to evaluate the predictive value of the first four weeks for the treatment outcomes. 2.

Methods

A detailed description of the study design, goals, population, assessment and measures has been given in Apelt et al. [2]. 2.1. Design of the study The study, conducted from 2008 to 2010, was - 88 -

a nationwide multicentre 12-month prospective, noninterventional, post-marketing safety study with 12 assessment points involving 384 opioid-dependent patients from 69 general practitioners, clinics and outpatient clinics in Germany. Opioid-dependent patients over 15 years of age with written informed consent and for whom the switch to buprenorphinenaloxone (BNX) was indicated and planned were eligible for selection. Therapeutic indications and contraindications of the Summary of Product Characterization (SmPC) for BNX had to be considered. The physician had full responsibility for deciding which patients should be enrolled, how the treatment with BNX was to be implemented and which BNX dosage should be applied. Altogether, 337 data sets were eligible for analysis. A detailed description of the methods used in the study and which datasets were excluded from the final analysis is given in Apelt et al [2]. 2.2. Assessment within the first four weeks The assessment was performed at day 0 before induction into, or a switch to BNX, at days 1, 2, 3, 5 and 7, and at the end of weeks 2 and 4 of treatment with BNX. An extensive clinical research form, completed by the treating physician, and four standardized questionnaires completed by the patients, were used to obtain comprehensive data on sociodemographics, substance use and addiction history, treatment history, comorbidities, co-medication, concomitant drug use, urine drug screening, reason for switching to BNX, details of BNX treatment, premature discontinuation before end of observation, effectiveness, withdrawal, craving, quality of life and safety. The physician’s questionnaire specially developed for the non-interventional study comprised evaluation tools to cover the sections mentioned above, including standardized instruments such as a modified version of the Clinical Global Impression scale (CGI) and the Objective Opiate Withdrawal Scale (OOWS) [17]. The patients’ questionnaires were the Short Form 36 – Health Survey (SF-36) [5], the Subjective Opiate Withdrawal Scale (SOWS) [17], the revised psychiatric Symptom Checklist (SCL-90R) [13] and, specially invented for the studyvisual analogue scales for craving [2]. 2.3. Aims The general aim of this evaluation was to find

S. M. Apelt et al.: Induction and switch to buprenorphine-naloxone in opioid dependence treatment: Predictive value of the first four weeks

predictors for treatment outcomes. The predictors specially selected for treatment outcomes were: • Screening phase (day 0): Gender, age, dose of prior maintenance drug for pre-treated patients, drug screening results, withdrawal and craving, psychiatric status, health-related quality of life. • Induction phase (days 1 to 7): Withdrawal and craving, dose of BNX. • Stabilization phase (weeks 2 to 4): Withdrawal and craving, psychiatric status, health-related quality of life, dose of BNX. 2.4. Statistics and Analyses The following groups were selected and will now be compared: 2.4.1.Retention Status • Positive Outcome (PO): Patients still in treatment with BNX at the end of observation (month 12) including patients with regular end of treatment before end of observation (patient abstinent) (n = 195) • Negative Outcome (NO): Patients with documented premature discontinuation of the treatment with BNX for any reason other than regular end of treatment (patient abstinent) before end of observation (month 12) (n = 142). Reasons for premature discontinuations were, for example: “lost to follow up” (16.7%), “concomitant drug use/relapse” (12.2 %), “side effects” (12.2%) and “non-compliance/disciplinary reasons” (10.9%) [2]. 2.4.2. Previous Drug: • MTD: Pre-treated patients switched from d/lmethadone (n = 51). • L-MTD: Pre-treated patients switched from levo-methadone (n = 24). • BUP: Pre-treated patients switched from the mono buprenorphine product (n = 162). • HER: Patients with no current maintenance treatment inducted BNX directly from heroin use (n = 93). Logistic regressions, analysis of variances or chi-square tests were used to analyse correlations between the defined patient groups and selected predictive parameters. Missing values and “no test” were both defined as positive results. The Kaplan-Meier method was used to estimate retention rates and times. For the determination of group differences in

retention rates, the log rank test was used. All statistical analyses were performed using STATA/SE 9.0 [29]. 3.

Results

3.1. Patient’s Characteristics Table 1 summarizes patients’ characteristics at day 0. Predictors of the screening phase for positive treatment outcome (PO) were: older age, stable relationship and own flat, or living with family members. Patients with PO had a longer drug dependence history and pre-treated patients had been significantly longer in their previous maintenance treatment before switching to BNX, especially those who had previously been BUP patients. Fewer withdrawal symptoms and less craving for opiates were further predictors forPO. By contrast, patients with negative treatment outcome (NO) were more likely to be single, homeless, hepatitis C-positive and more severely burdened with psychiatric comorbidity. They reported higher rates for craving and withdrawal at day 0. 3.2 Prior maintenance treatment The prior treatment status (i.e., whether the patient had been switched from a previous treatment, or had been inducted directly from active heroin use) had no impact on treatment outcome. Conversely, a patient switched from L-MTD had a higher chance of being retained in treatment with BNX for the complete 12 months of observation. A higher last dose of the prior maintenance drug before switching to BNX was a factor predictive for PO in patients switched from MTD and L-MTD. 3.3 Urine drug screening An overall lower total number of positive drug screenings at day 0 was predictive for PO (2.6±1.7 vs. 3.2±1.7 NO, p=.004, OR 0.83, 95%CI 0.72-0.94), particularly for opiates (33.3% vs. 45.8%, p=.021), cocaine (6.2% vs. 16.2%, p=.003) and benzodiazepines (21.0% vs. 35.9%, p=.002). A significant difference in the total number of positive drug screenings was only found in L-MTD patients (1.4±1.0 PO vs. 4.3±1.9 NO, p<.001, OR 0.23, 95%CI 0.06-0.79). 3.4 Dose of BNX Patients with NO started with slightly higher - 89 -


Table 1: Patients’ characteristics at baseline.

Age in years [mean (SD)] N = 336 Male [n (%)] N = 337 Marital status [n (%)] N = 334 - Single - Married/living with a partner - Divorced Occupation [n (%)] N = 337 - Employed - Unemployed Residential status [n (%)] N = 337 - Own flat/house or living with family - Homeless Years of dependence [mean (SD)] N = 311 Currently in substitution treatment [mean (SD] N = 337 Years of current substitution treatment [mean (SD] N = 213 - Buprenorphine - D/L-Methadone - Levo-Methadone Type of current substitution treatment [n (%)] - Buprenorphine - D/L-Methadone - Levo-Methadone Dose of prior substitution treatment [mean (SD)] - Buprenorphine (N = 161) - D/L-Methadone (N = 50) - Levo-Methadone (N = 23) Hepatitis C infection [n (%)] N = 335 HIV infection [n (%)] N = 272 Psychiatric comorbidity – physician’s assessment [n (%) N = 337 Number of psychiatric comorbidities [mean (SD)] N = 193 Psychiatric Status – SCL90R [mean (SD)] - GSI (N = 316) - PST (N = 321) - PSDI (N = 318) Withdrawal [mean (SD)] - Objective Opiate Withdrawal Scale (N = 337) - Subjective Opiate Withdrawal Scale (N = 325) Craving [mean (SD)] - Total Score (N = 325) - Opiate Craving (N = 323) Quality of Life – SF36 [mean (SD)]

Total Sample 337* 35.1±8.8 258 (76.6)

PO 195 36.0±9.0 154 (79.0)

NO 142 33.9±8.4 104 (73.2)

p .029 .220

201 (60.2) 102 (30.6) 30 (9.0)

108 (56.3) 69 (35.9) 14 (7.3)

93 (65.5) 33 (23.2) 16 (11.3)

.088 .013 .209

125 (37.1) 179 (53.1)

75 (38.5) 100 (51.3)

50 (35.2) 79 (55.6)

.542 .429

296 (87.8) 5 (1.5) 13.8 (8.7) 244 (72.4)

177 (90.8) 0 (0.0) 14.6 (8.5) 140 (71.8)

119 (83.8) 5 (3.5) 12.8 (8.8) 104 (73.2)

.053 .008 .077 .958

3.8±3.6

4.3±4.0

3.1±3.0

.022

4.2± 3.8 3.1± 3.1 3.3± 3.6

5.0± 4.3 3.1± 2.8 2.7± 3.0

3.0± 2.5 3.2± 3.6) 5.0± 4.7

.003 .931 .177

162 (66.4) 51 (20.9) 24 (9.8)

93 (66.4) 29 (20.7) 18 (12.9)

69 (66.4) 22 (21.2) 6 (5.8)

.989 .933 .066

7.7± 4.3 41.8± 37.2 26.5± 17.1 121 (36.1) 4 (1.2)

7.2± 4.1 53.6± 42.4 31.0± 16.2 62 (31.8) 2 (1.0)

8.4± 4.4 25.6± 20.1 10.2± 8.6 59 (42.1) 2 (1.4)

.088 .007 .013 .009 .637

193 (57.3)

106 (54.4)

87 (61.3)

.206

2.0± 1.5

1.9± 1.6

2.1± 1.5

.538

0.7± 0.6 37.0± 24.0 1.5± 0.5

0.7± 0.6 34.3± 24.5 1.5± 0.5

0.8± 0.6 40.5±23.1 1.6± 0.5

.051 .023 .161

8.8± 8.1 17.2± 13.5

8.4± 8.0 15.9± 13.4

9.4± 8.2 19.0± 13.6

.259 .043

12.4± 11.1 32.3± 33.2

10.2± 9.6 27.6± 30.9

15.4± 12.3 38.9± 35.4

<.001 .003

* Eligible datasets PO = Positive Treatment Outcome; NO = Negative Treatment Outcome

doses of BNX on day 1 of treatment. On day 2 the average dose increased in both groups. While the average dose in patients with PO already started to decrease on day 3, in patients with NO the average

- 90 -

dose was stable until day 7. In week four both groups reached almost the same average dose of their day of induction. “Clean” patients were excluded from this analy-


Table 1: Patients’ characteristics at baseline.

- Physical Health (N = 324) - Mental Health (N = 320) Positive Urine Drug Screening [n (%)] - Opiates (N = 331) - Cocaine (N = 330) - Cannabis (N = 252) - Benzodiazepines (N = 330) General Health – physician’s assessment mean (SD)] N = 335

Total Sample 337* 52.9± 18.6 50.8± 24.2

PO 195 54.3± 18.3 52.0± 25.1

NO 142 51.0± 18.9 49.0± 22.9

p .118 .277

124 (37.5) 28 (8.5) 83 (32.9) 85 (25.8)

60 (31.6) 6 (3.2) 45 (31.5) 37 (19.4)

64 (45,4) 22 (15.6) 38 (34.9) 48 (34.5)

.010 <.001 .570 .002

1.7± 1.0

1.7± 1.0

1.8± 1.0

.384

* Eligible datasets PO = Positive Treatment Outcome; NO = Negative Treatment Outcome

sis, because their dosing was significantly lower, and it also decreased more rapidly during the first four weeks; it therefore fails to reflect the expected normal course of dosing after induction, or switch to buprenorphine-naloxone. Figure 1 shows the average dose of BNX during the first four weeks of treatment (N = 323) If controlled for prior treatment/drug (see Table 2), there is no difference in dosing between PO and NO in patients switched from MTD or HER. Patients with PO switched from L-MTD received slightly lower doses of BNX on day 1 and considerably higher doses at week 4. The switch from BUP to BNX led to an average dose increase of 0.5 mg in both groups. However, BUP patients with PO received significantly lower doses of BNX. Table 2 shows dosing of BNX by previous drug

during the first four weeks of treatment No significant differences in dosing of BNX within the first four weeks were found concerning regions of Germany. Since only 3 outpatient clinics participated in the study, the type of setting was not analysed as a possible influencing factor. 3.5 Withdrawal To measure the signs and symptoms of opiate withdrawal, the subjective and objective opiate withdrawal scales (OWS) were used [17]. Lower opiate withdrawal predicted positive treatment outcome (PO). In the objective scale (OOWS) patients with PO received lower scores from day 3 to week 4, and in the subjective scale (SOWS) they achieved lower scores from day 2 to week 4. There were no differenc-

Figure 1. Average dose of BNX during the first four weeks of treatment (N = 323).

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Table 2: Dosing of BNX by previous maintenance treatment and previous drug, during the first four weeks of the study MTD (n = 51) L-MTD (n = 24) BUP (n = 162) HER (n = 93) PO NO p PO NO p PO NO p PO NO p Day 1 12.8 12.5 .793 8.2 11.0 .124 7.7 8.9 .066 9.2 8.7 .641 Day 2 13.3 12.8 .793 11.5 12.0 .857 7.8 9.3 .021 9.7 9.5 .855 Day 3 11.9 12.4 .724 12.4 12.0 .900 7.9 9.6 .021 9.6 9.6 .995 Day5 11.4 11.4 .960 12.1 12.0 .964 8.0 9.6 .028 9.4 9.7 .797 Day 7 10.8 10.6 .894 12.1 12.0 .964 7.9 9.9 .008 8.9 9.7 .440 Week 2 11.0 10.3 .450 11.9 10.7 .607 8.0 9.4 .070 8.5 9.7 .199 Week 4 10.6 10.3 .805 12.0 7.5 .083 7.9 9.3 .057 8.3 9.6 .226 MTD: Patients switched from d/l-methadone L-MTD: Patients switched from levo-methadone BUP: Patients switched from the mono-compound buprenorphine HER: Patients inducted directly from heroin use PO = Positive Treatment Outcome NO = Negative Treatment Outcome

es in withdrawal symptoms between the two groups in prior MTD patients. Prior L-MTD patients with PO showed significantly fewer objective withdrawal symptoms from day 3 to week 4. A similar pattern is found in the SOWS, with significantly lower withdrawal symptoms for patients with PO as early as day 2 of BNX treatment. According to the ratings given by the treating physicians, prior BUP patients with PO showed significantly fewer opiate withdrawal symptoms in the first two weeks of BNX treatment. Figure 2. Craving for opiates by previous substance

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By week 4, however, the difference was no longer significant compared with BUP patients with NO. The same pattern can be found in the scores from the self-assessment questionnaire SOWS for this group. Prior HER users with PO achieved significantly lower scores for opiate withdrawal between day 7 and week 4 of BNX treatment, but only on the subjective scale. According to physicians, neither group of HER users differed in terms of opiate withdrawal at screening and during the first four weeks of treatment with


BNX. 3.6 Craving for Opiates Craving was measured with the self-assessment 100 mm visual analogue scales for 12 substances [2]. Lower craving for opiates predicted PO in all three phases of the first four weeks of treatment with BNX. As shown in Figure 2, the significant difference between PO and NO is only found in patients previously treated with L-MTD or BUP. At screening and in the first two days of treatment with BNX, patients with PO previously treated with MTD experienced higher craving for opiates, but at the end of week 4 these patients experienced marginally lower craving. No differences in terms of craving were found in prior HER users. 3.7 Psychiatric Distress (SCL-90-R) The psychiatric distress status was measured with the standardized self-assessment tool SCL90-R. The Global Severity Index (GSI) is the best indicator for the current extent of overall psychiatric distress [13]. A lower value for this global scale at screening (0.7±0.7 vs. 0.8±0.6 NO, p=.051) and

week 4 (0.3±0.4 vs. 0.4±0.5, p=.030) predicted PO. The most severe forms of psychiatric distress were measured in L-MTD patients at screening for both groups (1.1±0.5 PO vs. 0.9±0.3 NO, p=.609) and at week 4 for patients with NO (0.3±0.3 vs. 0.6±0.4, p=.098). The mildest psychiatric distress was measured in BUP patients at screening for both groups (0.5±0.5 vs. 0.7±0.5, p=.004). MTD patients did not differ at screening or at week 4. At screening, prior HER users received scores that were similar to those of patients previously on MTD, with no differences between PO and NO, but at week 4 prior HER users with PO reported significantly milder psychiatric distress (0.3±0.3 vs. 0.5±0.5, p=.025). 3.8 Health-related Quality of Life (SF-36) The health-related quality of life (QoL) was evaluated with the self-assessment tool SF-36, which measures the subjective core indicators of physical and mental health [5]. No predictive value was found in the two global scales, physical and mental health. In any case, patients with positive treatment outcome (PO) achieved slightly higher scores in both global scales at screening (physical health: 54.3±18.3 PO vs. 51.0±18.9 NO, p=.118; mental health: 52.0±25.1 vs.

Figure 3. Kaplan-Meier Survival Curves by previous Drug

- 93 -


49.0±22.9, p=.277) and at week 4 (physical health: 62.9±13.3 vs. 60.1±14.7, p=.112; mental health: 65.6±20.0 vs. 61.8±20.9, p=.142). No differences at screening or in week 4 were found in patients switched from MTD, L-MTD or HER at screening, or at the end of week 4. But previous BUP patients with PO achieved significantly higher scores at screening (physical health: 62.8±14.4 vs. 54.8±17.6, p=.002; mental health: 64.6±21.7 vs. 53.8±23.7, p=.003). By week 4 the scores were no longer significant (physical health: 66.4±13.4 vs. 62.2±15.1, p=.093; mental health: 71.3±20.0 vs. 65.2±21.8, p=.098). As itemized within the nine single scales, higher scores in the scales for “physical role functioning” at week 4 (7.2±1.3 PO vs. 6.8±1.5 NO, p=.046), and for “pain” at screening (9.1±2.9 vs. 8.1±3.3, p=003) and week 4 (10.6±1.8 vs. 9.9±5.5, p=.010) predicted a positive treatment outcome (PO). The extent of improvement between baseline and week 4 was only predictive for L-MTD patients, but, conversely, neither for the total population nor for MTD, BUP or HER. L-MTD patients with PO achieved higher improvement scores in both global scales (physical health: improvement 23.1±11.8 PO vs. 4.3±6.5 NO, p=.008; mental health: improvement 40.2±20.8 vs. 10.8±9.7, p=.015) and again in the single scales for “physical functioning” (4.2±3.0 vs. 0.3±2.1, p=.024), “pain” (3.2±1.7 vs. -0.5±1.9, p=.001), “social functioning” (2.3±1.5 vs. -0.5±1.3, p=.004) and “emotional well-being” (7.4±4.6 vs. 7.8±2.6, p=.033). For BUP patients the only predictive value for PO was found in the scale for “drug dependence” (2.2±6.9 vs. 4.9±8.7, p=.049). 3.9 Retention and dropout The 4-weeks survival probability for the total population was 89.3%. One quarter (25.4%) of all patients with negative treatment outcome (NO) (n = 142) prematurely terminated treatment with BNX in the first four weeks, including 9 of the group during the first week. Figure 3 shows the survival probability by previous drug. The highest retention and lowest dropout rate in the first four weeks was found in prior MTD patients (13.6%). 24.6% of patients with NO in prior BUP patients and 23.7% of HER users dropped out of treatment during the first four weeks. Of prior LMTD patients, 2 out of 6 patients with NO terminated their treatment prematurely during the first 4 weeks. Log-rank test and logistic regression revealed no dif-

- 94 -

ferences in survival and treatment duration between the four previous drug groups. Patients with a maximum dose of ≤8 mg per day BNX during the first four weeks stayed significantly longer in treatment compared with patients with at least one dose of >8 mg per day during the first 4 weeks (Log-rank: χ2 = 3.78, p=.052; twosample t-test: mean retention 282.0±136.6 days vs. 241.1±149.2 days, t = 2.57, p=.011). Patients showing no cocaine use at screening stayed significantly longer in treatment than those with positive urine screening for any illicit drug (log-rank χ2 = 7.06, p=.008). Patients with negative urine screenings for opiates, cocaine and/or benzodiazepines had a significantly longer treatment duration than those with positive test results for all three substances (Log-rank χ2 = 5.08, p=.024). 4.

Discussion

The results of this study proved that opioid-dependent drug users are, indeed, an extremely heterogeneous group [32]. Most of the characteristics evaluated at baseline and during the first four weeks of treatment with buprenorphine-naloxone (BNX) are specific for certain patient groups, especially concerning prior substance and treatment experience. Despite all the individual differences, this evaluation found parameters that can be reliably used as signals to adjust the treatment plan, and influence course and outcome of opioid dependence treatment with BNX. The major challenge in drug-substitution treatment is to retain patients in treatment [6] and thus enable them to regain control over their lives [8, 10]. The overall 4-week retention rate was 89.3%, irrespective of whether the patient was switched from an ongoing maintenance treatment, or inducted directly from heroin use (HER). As found in previous studies, being older, treatment experienced, and showing no cocaine use at screening predicted higher chances of retention [1, 4, 15, 23, 24, 30]. In this study, employment status at screening had no significant impact on retention, but patients who had their own flat, or were still living at home with their family, seemed to benefit from a more stable living condition. By contrast, homeless patients had practically no chance of a positive treatment outcome. In previous studies, polydrug use predicted low retention and a high chance of dropout [6, 9, 20, 25, 30]. In this study this criterion only applied to patients switched from levo-methadone (L-MTD). Single negative test results for benzodiazepines, cocaine


or opiates at the screening phase were predictive for positive treatment outcomes in patients switched from BUP and L-MTD. Previous drug use clearly had no impact on retention or on dropout for patients switched from d/l-methadone (MTD) or inducted to BNX from active heroin use. Contrary to international findings on a positive correlation between higher doses of BNX (12-16mg) and high retention [7, 18, 19, 22], in this study a lower dose of BNX in the first four weeks (≤8 mg) predicted a higher level of retention. The reason might be that patients with a positive treatment outcome (PO) had, in general, a more favourable sociodemographic, medical and addiction history profile than those with a negative outcome (NO). Physicians seem to allocate their patients to a certain induction dose in line with specific patient characteristics such as social circumstances, physical and mental health, withdrawal and craving. The high probability of treatment retention in patients with a maximum dose of 8 mg per day during the first four weeks of treatment with BNX might be explained by the fact that these patients start their therapy from a more favourable level than those who received over 8 mg per day of BNX at least once during the first four weeks. At present this largely unexpected outcome cannot be adequately explained. It follows that this surprising finding calls for further detailed analysis after taking into account the impact of craving, withdrawal, and prior maintenance dose, as well as psychiatric distress, quality of life and other important parameters pertinent to the correlation between BNX dose and retention. In addition, in future studies the concerns of patients over the effects of naloxone in the combination product and the importance of the physician-patient relationship should become a focus of attention. Parameters assessed in the screening phase (day 0) have a high predictive value and should be studied for treatment planning by physicians. Still more importantly, week 4 of the stabilization phase in BNX treatment seems to play a major role in measuring predictive values for positive treatment outcomes and high chances of retention. Differences between patients with PO and NO were most frequently found in this phase. In particular, scores for psychiatric distress, withdrawal, craving and dosing of BNX differ strongly at week 4, and could therefore be used as signals for operative improvements to the treatment plan. As a result, the physician in charge should test these variables by applying standardized patient questionnaires at the end of the stabilization phase, so as to provide patients, who have rather unfavourable

characteristics, their best possible treatment setting. The predictive value of some of the variables only applied to patients switched from L-MTD, whereas for MTD patients almost none of the variables could be used as predictors at this early stage of BNX treatment. In addition, prior MTD patients and HER users did not differ in their characteristics at baseline, but HER users seemed to draw considerably more benefit from the BNX treatment than MTD patients. These findings support the suitability of BNX as a first-line medication for active heroin users. One of the limitations of the study might be the absence of a control group. Since the study did not examine the efficacy of BNX, but aimed to evaluate the safety and effectiveness of the switch from an ongoing maintenance treatment to BNX in routine care, this limitation is acceptable. Another limitation is the disproportionate distribution of patients to the prior treatment/drug group. The high predictive value for L-MTD patients might be due to their low number of only 24 patients. Future studies should be conducted with a higher, more evenly distributed number of patients to evaluate the switch from L-MTD, MTD and HER to BNX, and to generate more robust data. Another limitation might be the recruiting process: Only patients who agreed to participate in the study and signed the informed consent form were eligible for inclusion in the 12-month observation period. That leaves open the possibility of a positive selection bias. Patients who refused to participate, as well as those who were excluded from consideration as study candidates by the participating physician were not evaluated, and no comparison with the group of study participants in assessing certain parameters is possible. The major strength of the study is its authentic reflection of the real life situation in opioid dependence treatment in Germany. It was the sole responsibility of the physician who was in charge to decide which patients should be enrolled, how the treatment with BNX was to be implemented, and what dose of BNX the patients would receive. 5.

Conclusions

The first four weeks of BNX treatment after a switch from d/l-methadone, levo-methadone, buprenorphine or active heroin use have a high value in predicting a positive treatment outcome, especially with reference to the parameters: withdrawal, craving and psychiatric distress, to be measured at the screening phase (day 0), and at the end of the stabilization phase (week 4). These values need to be considered - 95 -


in close conjunction with age, current drug use, social status and treatment experience. For optimal treatment redefinition to raise the patient’s chances of being retained and of achieving a positive treatment outcome, the physician in charge needs to take into account whether the patient has been pre-treated with d/l-methadone, levo-methadone or buprenorphine, or whether the patient was inducted into BNX directly from heroin. Many predictive values seem to be unique to a subgroup of patients only. References 1. Alford, D. P., LaBelle, C. T., Kretsch, N., Bergeron, A., Winter, M., Botticelli, M., et al. (2011). Five Year Experience with Collaborative Care of Opioid Addicted Patients using Buprenorphine in Primary Care. Arch Intern Med., 171 (5): 425-431. 2. Apelt, S. M., Scherbaum, N., Gölz, J., Backmund, M., Soyka, M. (2013). Safety, Effectiveness and Tolerance of Opioid Dependence: Results from a Nationwide Non-Interventional Study in Routine Care. Pharmacopsychiatry, 46(03): 94-107. 3. Barnett, P., Rodgers, J., Bloch, D. (2001). A meta-analysis comparing buprenorphine to methadone for treatment of opiate dependence. Addiction (96): 683-690. 4. Borisova, N. N., Goodman, A. C. (2004). The effects of time and money prices on treatment attendance for methadone maintenance clients . Journal of Substance Abuse Treatment (26): 345-352. 5. Bullinger, M., Kirchberger, I. (1998). SF-36: Fragebogen zum Gesundheitszustand (Manual). Göttingen: Hogrefe. 6. Copenhave, M. M., Bruce, R. D., Altice, F. L. (2007). Behavioral Counseling Content for Optimizing the Use of Buprenorphine for Treatment of Opioid Dependence in Community-Based Settings: A Review of the Empirical Evidence . Am J Drug Alcohol Abuse, 33 (5): 643-654. 7. Cunningham, C., Giovanniello, A., Sacajiu, G., Whitley, S., Mund, P., Beil, R., et al. (2008). Buprenorphine Treatment in an Urban Community Health Center: What to Expect. Fam Med, 40 (7): 500–506. 8. Davids, E., Gastpar, M. (2004). Buprenorphine in the treatment of opioid dependence. European Neuropsychopharmacology (14): 209-216. 9. Downey, K. K., Helmus, T. C., Schuster, C. R. (2000). Treatment of Heroin-Dependent PolyDrug Abusers With Contingency Management and Buprenorphine Maintenance. Experimental and Clinical Psychopharmacology, 8 (2): 176-184. 10. EBDD. (Jan-Feb 2002). Drogen im Blickpunkt: Schlüsselrolle der Substitution in der Drogentherapie. From Europaeische Beobachtungsstelle für Drogen und Drogensucht: http://www.emcdda.org 11. Fiellin, D., Moore, B., Sullivan, L., Becker, W., Pantalon, M., Chawarski, M., et al. (2008). Long-Term Treatment with Buprenorphine/Naloxone in Primary Care: Results

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at 2-5 Years. The American Journal on Addictions 17: 116-120. 12. Fischer, G., Gombas, W., Eder, H., Jagsch, R., Stühlinger, G., Aschauer, H., et al. (1999). Vergleichsuntersuchung Buprenorphine und Methadon im Rahmen der Erhaltungstherapie Opiatkranker. Nervenarzt (70): 795802. 13. Franke, G. H. (2002). SCL-90-R: Symptom Checkliste von L. R. Derogatis - German Version -. Göttingen: Beltz Test GmbH. 14. Fudala, P. J., Bridge, P., Herbert, S., Williford, W. O., Chiang, N., Jones, K., et al. (2003). Office-Based Treatment of Opiate Addiction with a Sublingual-Tablet Formulation of Buprenorphine and Naloxone. The New England Journal of Medicine, 349 (10): 949-958. 15. George, W., Joe, D., Simpson, D., Broome, K. (1998). Effects of readiness for drug abuse treatment on client retention and assessment of process. Addiction, 93 (8): 1177-1187.) 16. Greenwald, M. K., Johanson, C.-E., Moody, D. E., Woods, J. H., Kilbourn, M. R., Koeppe, R. A., et al. (2003). Effects of Buprenoprhine Maintenance Dose on mu-Opioid Receptor Availability, Plasma Concentrations, and Antagonist Blockade in HeroinDependent Volunteers. Neurpsychopharmacology (28): 2000-2009. 17. Handelsman, L., Cochrane, K., Aronson, M., Ness, R., Rubinstein, K., Kanof, P. (1987). Two New Rating Scales for Opiate Withdrawal. The American Journal of Drug and Alcohol Abuse, 13 (3): 293-308. 18. Kamien, J. B., Branstetter, S. A., Amass, L. (2008). Buprenorphine-Naloxone Versus Methadone Maintenance Therapy: A Randomised Double-Blind Trial with Opioid-Dependent Patients. Heroin Addict Relat Clin Probl, 10 (4): 5-18. 19. Kraus, S. W., Logan, M. E. (2009). Examining Buprenorphine Retention in a Rural Solo Addition Medicine Practice: A Retrospective File Review . Research and Practice in Social Sciences, 4 (2): 14-26. 20. Krook, A. L., Brørs, O., Dahlberg, J., Grouff, K., Magnus, P., Røysamb, E., et al. (2002). A placebo-controlled study of high dose buprenorphine in opiate dependents waiting for medication-assisted rehabilitation in Oslo, Norway. Addiction (97): 533-542. 21. Küfner, H., Hackmann, K., Schnabel, A., Soyka, M. (2004). Optimierung der substitutionsgestützen Therapie Drogenabhängiger (OSTD): Entzugssymptome und Suchtverlangen in der ersten Einstellungswoche. Suchtmed, 6 (1): 95-97. 22. Ling, W., Charuvastra, C., Collins, J., Batki, S., Brown, L., Kintaudi, P., et al. (1998). Buprenoprhine maintenance treatment of opiate dependence: a multicenter, randomized clinical trial. Addiction (93): 475-586. 23. Maremmani, I., Pacini, M., Lamanna, F., Pani, P. P., Trogu, M., Perugi, G., et al. (2008). Predictors for Non-Relapsing Status in Methadone-Maintained Heroin Addicts. A Long-Term Perspective Study . Heroin Addict


Relat Clin Probl, 10 (4): 19-28. 24. Mintzer, I. L., Eisenberg, M., Terra, M., MacVane, C., Himmelstein, D. U., Woolhandler, S. (2007). Treating Opioid Addiction With Buprenorphine-Naloxone in Community- Based Primary Care Settings. ANNALS OF FAMILY MEDICINE, 5 (2): 156-150. 25. Oehlin, L., Hesse, M., Fridell, M., Taetting, P. (2011). Poly-substance use and antisocial personality traits at admission predict cumulative retention in a buprenorphine programme with mandatory work and high compliance profile. From BioMed Central Ltd.: http://www.biomedcentral.com/1471-244X/11/81 26. Somaini, L., Giaroni, C., Gerra, G. (2008). Opioid Therapy and Restoration of the Immune Function in Heroin-Addicted Patients. Heroin Addict Relat Clin Probl, 10 (4): 39-44. 27. Soyka, M., Kranzler, H., van den Bring, W., Krystal, J., Möller, H.-J., Kasper, S. (2011). The World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for Biological Treatment of Substance Use and Related Disorders. Part 2: Opioid Dependence. World Journal of Biological Psychiatry, 12 (3): 160-187. 28. Soyka, M., Träder, A., Klotsche, J., Haberthür, A., Bühringer, G., Rehm, J., et al. (2012). Criminal Behavior in Opioid-Dependent Patients Before and During Maintenance Therapy: 6-year Follow-Up of a Nationally Representative Cohort Sample. Journal of Forensic Sciences, doi: 10.1111/j.1556-4029.2012.02234.x. 29. Stata Corp. (2005). Stata Statistical Software: Release 9. College Station, TX: StataCorp LP. 30. Stein, M. D., Cioe, P., Friedmann, P. D. (2005). Buprenorphine retention in primary care. J Gen Intern Med (20): 1038–1041. 31. Stoller, K. B., Bigelow, G. E., Walsh, S. L., Strain, E. C. (2001). Effexts of buprenorphine/naloxone in opioid-dependent humans. Psychopharmacology (154): 230-242. 32. Wittchen, H.-U., Apelt, S., Bühringer, G., Gastpar, M., Backmund, M., Gölz, J., et al. (2005). Buprenorphine and methadone in the treatment of opioid dependence: methods and design of the COBRA study. International Journal of Methods in Psychiatric Research, 14 (1): 1428.

Role of the funding source The original study was part of the Risk Management Plan (RMP) for the newly marketed product buprenorphine-naloxone (Suboxone®) and a requirement of the European Medicine Agency (EMA). The study is registered with the National Institute of Health (NIH) at clinicaltrials.gov (NCT00723749). Essex Pharma GmbH & Reckitt Benckiser Pharmaceuticals conducted this strictly observational, non-interventional study. All physicians received honoraria for the additional effort to document the start and course of the treatment with buprenorphine-naloxone in the comprehensive paper-based clinical research form. The honoraria were in line with the German medical fee schedule (Gebührenordnung für Ärzte, GOÄ), which controls the invoicing of medical attendance outside of the statutory health insurance. Contributors All authors contributed to and have approved the final manuscript. Conflict of interest Sabine M. Apelt has a financial interest/arrangement or affiliation with one or more organizations that could be perceived as a real or apparent conflict of interest in the context of the subject of this presentation. She receives or has in the past 3 years received honoraria from: Schering Plough, Essex Pharma GmbH, MSD SHARP DOHME GmbH and Reckitt Benckiser Pharmaceuticals. In the past three years Norbert Scherbaum received honoraria from Essex Pharma GmbH, Reckitt Benckiser Pharmaceuticals, Molteni and Sanofi-Aventis. For the past five years Michael Soyka has received travel grants, unrestricted research funding or has worked as a consultant for Presspharm, Reckitt Benckiser, Lilly, Astra Zeneca, Roche, Essex Pharma GmbH, Lundbeck and Sanofi Aventis.

Received February 22, 2014 - Accepted July 3, 2014 - 97 -

Letter to the Editor Heroin Addict Relat Clin Probl 2014; 16(3): 99-102

Using oral or i/m morphine for rapid tolerance assessment in patients starting methadone maintenance: A proposal for discussion based on over 25 years of experience Colin Brewer The Stapleford Centre. London, UK, EU

TO THE EDITOR: For many years, the standard advice and practice for starting patients on Methadone Maintenance Treatment (MMT) has been to ‘start low and go slow’. This is supposed to protect patients against overdose and death from either over-estimating tolerance to the initial dose or from cumulation after successive doses of a drug with a long half-life. However, deaths still occur and postmortem usually reveals significant levels of both heroin and methadone, probably because the ‘start low’ methadone dose is not enough to prevent significant withdrawal distress. In a patient with relatively modest or even borderline levels of tolerance, using even modest amounts of heroin on top of the methadone may prove fatal. This is unlikely to happen to patients with higher levels of tolerance. I want to argue here that this approach, while understandable historically and politically, is unnecessary and condemns many patients to seriously inadequate treatment in the early stages. This, in turn, forces many of them to continue using illicit opiates at precisely the time when motivation to stop using them is often high. In some cases, continued illicit use will lead to arrest and even incarceration, just when the patient has accepted that treatment is indicated and requests it. An alternative, at least in Britain, is to use a shorter-acting opiate to establish approximate levels

of tolerance to agonists and then convert the dosage needed to methadone. At one time, this had to be done on a rather empirical basis but in the past decade, there have been several trials of oral morphine (OM) as an alternative to methadone in patients for whom MMT caused unpleasant side effects. All of them show that many MMT patients who dislike methadone do, in fact, feel better on OM. However, what all of them also show (and the most important finding in this context) is that the ratio of OM to methadone, expressed as 24-hour equivalents, is remarkably consistent at an average of around 6:1, with most studies falling between 6:1 and 8:1. [1-9]. The proposed alternative – safely used by me and several colleagues in several hundred patients since about 1988 – means that a new MMT patient arriving at a clinic in slight withdrawal, as is usually advised, can be given repeated doses of oral morphine, under observation, over a period of a few hours until pupil size and other objective manifestations of opiate withdrawal have normalised. The process can be shortened by using repeated i/m injections, especially in patients who normally use the i/v route. Take, for example, a patient who claims a typical street heroin habit of 0.5g/day. In Britain, with heroin typically around 40% pure, this usually means around 200mg of diamorphine/24hrs. This corresponds roughly to 4-500mg of morphine/24hrs, or 100-125mg four times daily. (Some widely-used opiate equivalence tables calculate only single-

Corresponding author: Colin Brewer, The Stapleford Centre, London, UK, EU E-mail: [email protected]

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dose equivalents of methadone and do not give the 24-hour equivalents of opiates with a short half-life.) For comparison, a typical post-operative analgesic dose of morphine in a 70kg non-tolerant person will be 20-30mg i/m. If the patient is in obvious withdrawal, he/she will almost certainly have some tolerance but a test dose of 2030mg will quickly demonstrate it since in such cases, it will have little or no agonist effect. Further doses of 30-60mg of morphine at 30-40 minute intervals (orally) or 10-15 minute intervals (i/m) will confirm approximate levels of tolerance within a single morning or afternoon clinic session. This approximate tolerance can then be confidently converted to an equivalent dose of methadone, between 1/6 and 1/8 of the 24-hour morphine equivalent. It can safely be administered a few hours later in the same day as the effects of the morphine test dose wear off. Observing the patient for an hour or two after the methadone dose will further confirm tolerance. Even if a very cautious attitude means that only 60-70% of that dose is given on the first day, it will be much nearer the desirable maintenance dose than the 2030mg that is conventionally recommended. This approach is particularly helpful for the quite numerous patients with high tolerance who take large doses of heroin. Instead of having their methadone dose gradually increased over several weeks, it can be correctly titrated against objective clinical signs within a week. While the law in some countries prevents the use of morphine in this way, I believe the same technique can be used with dihydrocodeine, which is not a restricted opiate in most countries and, like morphine, is generally available in both oral and parenteral preparations. I shall be presenting a paper on this topic at the May 2014 EUROPAD meeting in Glasgow and this letter is intended to give both critics and supporters of my proposal plenty of time to study the relevant literature; and perhaps even to try the technique for themselves. References 1. Bond A. J., Reed K. D., Beavan P., Strang J. (2012): After the randomised injectable opiate treatment trial: post-trial investigation of slow-release oral morphine as an alternative

2.

3.

4.

5.

6.

7.

8.

9.

opiate maintenance medication. Drug Alcohol Rev. 31(4): 492-498. Fischer G., Jagsch R., Eder H., Gombas W., Etzersdorfer P., Schmidl-Mohl K., Schatten C., Weninger M., Aschauer H. N. (1999): Comparison of methadone and slow-release morphine maintenance in pregnant addicts. Addiction. 94(2): 231-239. Giacomuzzi S., Kemmler G., Ertl M., Riemer Y. (2006): Opioid addicts at admission vs. slow-release oral morphine, methadone, and sublingual buprenorphine maintenance treatment participants. Subst Use Misuse. 41(2): 223-244. Kastelic A., Dubajic G., Strbad E. (2008): Slow-release oral morphine for maintenance treatment of opioid addicts intolerant to methadone or with inadequate withdrawal suppression. Addiction. 103(11): 1837-1846. Madlung-Kratzer E., Spitzer B., Brosch R., Dunkel D., Haring C. (2009): A double-blind, randomized, parallel group study to compare the efficacy, safety and tolerability of slow-release oral morphine versus methadone in opioid-dependent inpatients willing to undergo detoxification. Addiction. 104(9): 1549-1557. Mitchell T. B., White J. M., Somogyi A. A., Bochner F. (2004): Slow-release oral morphine versus methadone: a crossover comparison of patient outcomes and acceptability as maintenance pharmacotherapies for opioid dependence. Addiction. 99(8): 940-945. Vasilev G. N., Alexieva D. Z., Pavlova R. Z. (2006): Safety and efficacy of oral slow release morphine for maintenance treatment in heroin addicts: a 6-month open noncomparative study. Eur Addict Res. 12(2): 53-60. Verthein U., Haasen C., Reimer J. (2012): Maintenance treatment for opioid dependence with slow-release oral morphine versus methadone: a randomized cross-over study. Presented at International Society of Addiction Medicine Annual Meeting, Geneva. Winklbaur B., Jagsch R., Ebner N., Thau K., Fischer G. (2008): Quality of life in patients receiving opioid maintenance therapy. A comparative study of slow-release morphine versus methadone treatment. Eur Addict Res. 14(2): 99-105.

Role of the funding source None. Conflict of interest None.

Received and Accepted December 13, 2013 - 100 -

Letter to the Editor Heroin Addict Relat Clin Probl 2014; 16(3): 103-106

30 years of Naloxone Massimo Barra and Vittorio Lelli Villa Maraini, Italian Red Cross (CRI), Rome, Italy, EU

TO THE EDITOR: Since August 1976, when we started our therapeutic activities at the Villa Maraini Foundation in Rome, our team has considered the safeguarding of drug users’ lives as being the top priority of any antidrug intervention. The ancient Romans used to say:“primum vivere, deinde philosophari”, meaning:“first survive, then theorize”. So, if you want to treat a drug user, he/ she has to be alive! At that time, naloxone was not available in Italy, whereas nalorphine was; this substance, which is an opioid antagonist, can only be taken under medical supervision, because of possible breathing depression which can arise if an overdose has been caused by the use of a mixture of opioids and other substances that depress the central nervous system. The arrival of naloxone, which does not present any such negative effect, made us think about its possible use by specifically trained non-medical staff. We learnt that naloxone is probably the only medication in the pharmacopoeia which is free from contraindications. Being a pure antagonist of opium derivates, it can save life in a case of heroin overdose, while it has no negative consequences in any other case: of course, it can provoke a temporary withdrawal syndrome, if the patient in question has a physical dependence on heroin. As early as 1980, during the first meeting that took place in Strasbourg from 19th till 21st May, the Red Cross/Red Crescent international group of drug

experts run by us considered “[...] the possibility of including this specific opioid antagonist in the Red Cross/Red Crescent first aid kits, while training first aiders, including volunteers, in the use of that substance. This is possible because that life-saving medicine for drug users [i.e. naloxone] is free from contraindications [...]” (Figure 1). Since then, thanks to our intense and evidencebased advocacy action, we have succeeded in reaching the point where naloxone is considered a lifesaving medicine, which has to be available in any pharmacy without a prescription. At the beginning, this was a unique case – together with saline liquid, distilled water and immunizing serum for viper poison – of an injectable substance in a phial being sold ‘over the counter’. Lately, thr immunizing serum was made subject to the medical prescription regime because of contraindications that had been noted in the meantime. In the 80’s and 90’s, many people were against the proposal that non-medical staff could be allowed to administer naloxone, considering this to be exclusively a medical act. Even the nurses of the Italian RC emergency units considered the use of naloxone as falling outside their sphere of competence. But we supported, and still support, the idea that a state of necessity may actually justify the violation of laws, if this is the only way to prevent a death that is otherwise inevitable. We assume that a credible antidrug strategy

Corresponding author: Massimo Barra, MD, Fondazione "Villa Maraini", via Bernardino Ramazzini, 31, 00151 Roma, Italy, EU Phone: +39 06 6575 3058; E-mail: [email protected]

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Figure 1. 1980 International Red Cross Statement

should be able to reach as many drug users as possible. Antidrug centres should adopt any possible initiative in order to guarantee full access to patients; currently that is not happening in far too many parts of the world. Anyone who goes to an antidrug centre is more motivated than someone who does not. Antidrug centres’ services should reach out to drug users in the streets, where they live out their daily tragedy. That is why, since March 25th, 1992 we have set up an emergency service, which is operational twenty-four hours every day, and has two mobile units that can quickly reach areas highly exposed to drug trafficking and drug use. In a case of overdose, first aid intervention at a hospital might not be enough, because the patient could be dead on arrival there. This is the reason why we need to use naloxone in a timely way – in the streets, at home and wherever an overdose occurs.

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By now there are many situations similar to “shooting rooms”, even if they are illegal in Italy. Many drug users, even those not motivated for treatment and rehabilitation, ask the staff of these mobile units for sterilized injection kits, often informing them about where they will take drugs. In this way we can intervene in cases of overdose. Many of these drug users are trained to use naloxone, in the sense that they receive elements of advice on overdose prevention; besides, those considered most exposed to overdose are periodically provided with two naloxone phials. This health education, together with the distribution of naloxone phials, is also addressed to drug users’ parents, relatives, friends and anybody else who is interested. During such training sessions, we point out that overdose risk normally increases after periods of prolonged abstinence related to detention or detoxication. In fact, we explain that, in such cases, doses have to be adapted, by considering the fall in tolera-

M. Barra &V. Lelli: 30 years of Naloxone

tion levels. It has to be considered that physical detoxification does not cover all the therapeutic requirements of a drug addict; it may not even be suitable, or actually dangerous. For example, wealthy drug addicts, in an attempt to safeguard their own reputation, often resort to temporary remedies, such as detoxification, instead of undergoing the ordinary treatment based on methadone or buprenorphine therapies, because their privileged social position make them think that an expensive detoxification treatment will be more effective than a low-cost therapy. However, these interventions, which can clean a drug user in a few weeks, or even in a few days, do not allow any control over the development of the addiction, because there is the factor of exposing the patient to a high risk of overdose. The overdose risk also increases in connection with: • 1. A combined intake of heroin together with other depressants such as alcohol; • 2. Any use of the drug when alone, whether at home or in hard-to-reach places; • 3. New dealers; • 4. The use of heroin that is too pure or of bad quality. Our experience in the field has shown us that, contrary to common beliefs, long-lasting drug users are more exposed to the risk of overdose than younger ones; furthermore, we have noted that, in certain areas, overdose cases normally occur in three or four episodes, with only short time-lapses in between, followed by a sequence of other days in which no further episodes are recorded. Only a few grams of heroin are needed to provide many people with their own dose and, if it is badly prepared or too pure, that will easily result in an overdose situation. In August 1995, the death of 6 people in Palermo, occurring within a few hours, due to heroin that had arrived in that city in an excessively pure state, represents a striking case in that sense. The local government representative as well as the mayor asked us for immediate intervention and, already on the first day, we saved 6 drug users in a state of overdose and more than a hundred in the following 3 months. In cases of overdose, our protocol prescribes an

immediate intramuscular injection of two naloxone phials; if the skin is hard to reach, the injection has, whenever necessary, to be performed through the clothes. After this first intervention the next step must be diversified to take into account the age and medical condition of the patient. For young drug users, for whom it is normally easy to find an accessible vein, we perform an intravenous injection of naloxone, which can be repeated a number of times. For long-lasting drug users, instead, we inject a further phial of naloxone under the tongue, because in their case suitable veins are normally hard to find, and unsuitable ones often give rise to occlusions in needles. From the beginning of our outreach work until 31st December 2013, we carried out 2,139 overdose interventions, all of them duly recorded, saving as many drug users’ lives. In addition, there are many interventions that cannot be quantified exactly because they are merely reported by drug users who have been previously instructed, and provided with naloxone phials by Villa Maraini. As pointed out above, so far we have never noted contraindications in the use of naloxone. We therefore see it as being the most effective measure for preventing the lethal consequences of opiate overdoses. We claim to have been the first practitioners in the world to theorize the use of injected naloxone by non-medical staff for overdose prevention, and to have performed the highest number of successful overdose interventions in non-medical settings. Role of the funding source No sponsor for this letter Contributors Authors revised and approved the final form of the letter. Conflict of interest Authors declared no conflict of interest.

Received and Accepted April 3, 2014 - 103 -

Forum Sunday, March 29, 2015 EUROPEAN OPIATE ADDICTION TREATMENT ASSOCIATION (EUROPAD) WFTOD meeting during AATOD Conference: EUROPAD Forum TIME: 13:00 - 17:00

Chairman: Icro Maremmani, MD (Pisa, Italy, EU) 13:00-13:20 The misuse: a part of opioid maintenance treatment A. Deschenau, D. Touzeau (Villejuif, France, EU) 13:20-13:40 Measuring outcomes in opioid dependence care: expert consensus on need for improved outcome measurement tools I. Maremmani (Pisa, Italy, EU), H. Alho (Helsinki, Finland, EU), R. Littlewood (London, UK) 13:40-14:00 Agonist Opioid Treatment and sexual dysfunctions L. Somaini (Biella, Italy, EU) 14:00-14:20 Replacement therapy method resettlement in prisons - yes or no? S. Kasper, J. Softic, H. R. Awad (Zenica, Bosnia & Erzegovina) 14:20-14:40 Emerging trends in alternative routes reported for prescription drug misuse: An international perspective J. Green (Denver, CO, USA) 14:40-15:00 Motivational interviewing to facilitate 12 Steps for Opiate Addiction S. R. Andrew (Portland, ME, USA) 15:00-15:20 Treatment of chronic hepatitis C in drug users : ethic, successful and useful A.J. Remy, H. Wenger, H. Bouchkira (Perpignan, France, EU) 15:20-15:40 Factors associated with outcome of inpatient opioid addiction treatment M. Delic, L. Lusa, P. Pregelj (Ljubljana, Slovenia, EU) 15:40-16:00 Risk factors for weight gain during Methadone Maintenance Treatment E. Peles, S. Schreiber, A. Sason, M. Adelson (Tel Aviv, Israel) 16:00-16:20 Introducing a Naloxone nasal-spray project as part of a national overdose prevention campaign in Norway; first experiences and results T. Clausen (Oslo, Norway) 16:20-17:00

Question time

Scientific Secretariat EUROPAD Committee http://www.europad.org/board-of-directors.php

Walking on Red Square, Moscow, Russia, January 2006

© Icro Maremmani

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