Drug and Alcohol Dependence 136 (2014) 36–42

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Randomized clinical trial of disulfiram for cocaine dependence or abuse during buprenorphine treatment Richard S. Schottenfeld a,∗ , Marek C. Chawarski a , Joseph F. Cubells b , Tony P. George c , Jaakko Lappalainen a , Thomas R. Kosten d a

Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States Departments of Genetics and Psychiatry and Behavioral Sciences, Emory University School of Medicine, United States c Division of Brain and Therapeutics, Department of Psychiatry, University of Toronto, Faculty of Medicine, Canada d Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine and Michael E. DeBakey VA Medical Center, United States b

a r t i c l e

i n f o

Article history: Received 1 November 2012 Received in revised form 10 December 2013 Accepted 10 December 2013 Available online 25 December 2013 Keywords: Cocaine abuse or dependence Disulfiram Buprenorphine pharmacogenetics DBH genotype

a b s t r a c t Background: Disulfiram may be efficacious for treating cocaine dependence or abuse, possibly through inhibiting dopamine ␤-hydroxylase (D␤H). Consequently, this randomized, placebo-controlled clinical trial of disulfiram during buprenorphine maintenance treatment evaluated the study hypothesis that disulfiram is superior to placebo and explored whether disulfiram response is greatest for participants with a single nucleotide polymorphism coding for genetically low D␤H (T-allele carriers). Methods: We randomized 177 buprenorphine-treated opioid dependent participants with cocaine dependence or abuse to 12 weeks of double-blind treatment with disulfiram 250 mg daily (n = 91) or placebo (n = 86). Of 155 participants genotyped, 84 were CC-homozygous, and 71 CT or TT genotypes. Primary outcomes included days per week cocaine use, number of cocaine-negative urine tests, and maximum consecutive weeks of cocaine abstinence. We analyzed an intention-to-treat comparison between disulfiram and placebo. We also explored potential pharmacogenetic interactions and examined treatment responses of four participant groups based on medication (disulfiram or placebo) by genotype (CC-homozygous or T-allele carrier) classification. Results: Disulfiram participants reported significantly less frequent cocaine use; the differences in cocaine-negative urine tests or consecutive weeks abstinence were not significant. Frequency of cocaine use was lowest in disulfiram-treated T-allele carriers; differences in cocaine-negative urine tests or consecutive weeks abstinence were not significant among the four medication-genotype groups. Conclusions: The findings provide limited support for the efficacy of disulfiram for reducing cocaine use and suggest that its mechanism of action may involve inhibition of D␤H. Further studies of its efficacy, mechanism of action, and pharmacogenetics of response are warranted. © 2014 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Cocaine abuse and dependence are significant public health problems, affecting an estimated 1.6 million Americans and 30–80% of opioid agonist maintained patients, including an increasing number treated in office-based settings with buprenorphine maintenance treatment (BMT; Arfken et al., 2010; Hubbard et al., 1997; Leri et al., 2003; Substance Abuse and Mental Health Services Administration, 2008). Cocaine use disorders are associated with a wide range of adverse health, social, family and legal consequences and, among opioid dependent patients, undermine the

∗ Corresponding author at: Yale University School of Medicine, 34 Park St. S205, New Haven, CT 06519. Tel.: +1 203 974 7349; fax: +1 203 974 7606. E-mail address: [email protected] (R.S. Schottenfeld). 0376-8716/$ – see front matter © 2014 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.drugalcdep.2013.12.007

effectiveness of opioid agonist maintenance treatment and increase risk for HIV infection (Bux et al., 1995; Chaisson et al., 1989; Haddad et al., 2013; Hartel et al., 1995; Hunt et al., 1986; Joe and Simpson, 1995; Kolar et al., 1990; Kosten et al., 1987, 1988; Wasserman et al., 1998). Currently, there are no established pharmacological treatments for cocaine use disorders or adjuncitve pharmacological treatments for opioid agonist maintained patients with co-occurring opioid dependence and cocaine abuse or dependence. Convergent epidemiologic, laboratory and clinical trial findings support the potential efficacy of disulfiram for treating cocaine use disorders, including some clinical trials with methadone maintained individuals and one small pilot study conducting during BMT (Baker et al., 2007; Bourdélat-Parks et al., 2005; Carroll et al., 2004, 1998; George et al., 2000; Hameedi et al., 1995; Kalayasiri et al., 2007; Major et al., 1979; McCance-Katz et al., 1998a,b; Oliveto et al., 2011; Pani et al., 2010; Petrakis et al., 2000; Schank et al.,

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2006; Schroeder et al., 2010). While initially evaluated because of the high co-morbidity of alcohol abuse among cocaine dependent individuals (Carroll et al., 1993, 1998), the effects of disulfiram on cocaine use are independent of reductions in alcohol use, suggesting that other mechanisms are involved (Carroll et al., 2004). One intriguing possibility is that disulfiram effects on cocaine use may involve inhibition of dopamine ␤- hydroxylase (D␤H), which occurs at the same clinically relevant disulfiram concentrations as inhibition of aldehyde dehydrogenase (Mays et al., 1998). D␤H catalyzes dopamine (DA) conversion to norepinephrine (NE); inhibition of D␤H elevates the DA/NE ratio in mesolimbocortical dopaminergic and noradrenergic pathways (Goldstein et al., 1964; Karamanakos et al., 2001; Stanley et al., 1997). Identification of a relatively common single nucleotide polymorphism (SNP) in the promoter region of the gene locus encoding D␤H (locus name: DBH) (−1021C→T) has provided an opportunity to explore whether disulfiram’s effects on cocaine result from inhibition of D␤H and whether response to disulfiram is affected by DBH genotype. The CC homozygotes at the SNP have approximately 6–10 fold higher plasma D␤H activity compared to TT homozygotes; CT heterozygous individuals have activity level that is midway between CC and TT homozygote individuals (Zabetian et al., 2001). Neuropsychiatric effects of disulfiram are more pronounced among individuals with lower baseline D␤H activity or the SNP coding for lower D␤H activity (Bourdélat-Parks et al., 2005; Ewing et al., 1977, 1978; Major et al., 1979). If disulfiram effects on cocaine use are mediated by its effects on D␤H, T-allele carriers might have the best response to disulfiram, since disulfiram may reduce D␤H activity to a sufficiently low level in these individuals to obtain clinically significant effects. Because preliminary evidence for the efficacy of disulfiram for reducing cocaine use during buprenorphine maintenance treatment comes from only one small pilot study, we conducted a randomized, double-blind, placebo-controlled clinical trial of disulfiram with a substantially larger sample size of individuals with co-occurring opioid dependence and cocaine abuse or dependence receiving buprenorphine maintenance treatment. We hypothesized that disulfiram is superior to placebo. The study also explored whether the response to disulfiram 250 mg daily differed between T-allele carriers and CC-homozygous individuals. 2. Materials and methods

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participants completed buprenorphine induction and stabilization and were randomized to treatment. 2.2. Randomization and blinding A research pharmacist who had no direct contact with participants used a computer-generated simple randomization list to allocate participants to active or placebo disulfiram. The research pharmacist prepared active disulfiram 250 mg and matching placebo capsules by filling identical blue 00 capsules with Avicel (microcrystalline cellulose, NF) only or Avicel mixed with pulverized disulfiram 250 mg tablets, purchased from a local pharmacy, and dispensed the medications in individual medication bottles prepared for each participant. The medication labeling was identical for bottles containing active or placebo disulfiram. With the exception of the research pharmacist, none of the other research personnel or care providers had access to the randomization list, which was kept in the locked pharmacy office. All participants were advised that they might receive disulfiram, educated about alcohol–disulfiram interactions, and warned about using alcohol or alcoholcontaining preparations. 2.3. Treatment procedures Buprenorphine and active or placebo disulfiram were ingested by participants under direct observation at the clinic six days per week (Monday–Saturday); participants were provided a single-day’s dosage of buprenorphine and active or placebo disulfiram for take-home medications for Sundays or holidays on the preceding day. All participants received one 8 mg SL buprenrophine mono tablet daily for the first three days, increased to two 8 mg SL tablets on days 4–7, and were then maintained on three 8 mg SL buprenorphine tablets (24 mg SL daily) through week 14. At the beginning of week 15, participants who did not want a referral for continuing buprenorphine or methadone maintenance or other available treatment began buprenorphine tapering at a rate of 4 mg every two days until the medication was discontinued and subjects were discharged. Participants received active or placebo disulfiram capsules daily beginning on the day of randomization and continuing through week 14. All participants also attended weekly manual-guided group drug counseling throughout the study period (Mercer and Woody, 1999). 2.4. Assessments Substance use was assessed by weekly self-report, obtained by a trained research assistant, using a time-line follow-back methodology (Sobell et al., 1988, 1986) to assess days per week using illicit opioids, cocaine, other drugs or alcohol, and by urine toxicology testing. Urine samples were obtained three times per week (at times of medication dispensing), temperature checked to detect tampering, and analyzed using the Abbott Tdx system with cut off points >200 ng/ml for opioids and >300 ng/ml for cocaine metabolite and benzoylecognine. Breath alcohol was assessed weekly. Adverse medication effects and medical symptoms were assessed weekly using a 33-item symptom checklist developed for the study; the checklist included common medical symptoms (e.g., sore throat), symptoms associated with opioid agonist medications (e.g., sweating) or withdrawal (e.g., diarrhea), and known adverse effects of disulfiram (e.g., headache, lethargy, numbness or tingling of the extremities, or visual disturbances).

The study design was a single site, randomized, double-blind clinical trial comparing 12 weeks of treatment with disulfiram (250 mg daily) or placebo. Participants were inducted and stabilized on buprenorphine over a 2-week period, before being randomized to disulfiram or placebo. Participant recruitment, treatment and assessments were conducted between October, 2000 and February, 2004 in an ambulatory drug abuse treatment research clinic in New Haven, CT. The study was approved by the Human Investigation Committee, Yale University School of Medicine. All participants gave written informed consent. The study was registered with Clinical trials.gov (NCT00913484).

DNA (available from 155 participants) was extracted from whole blood using the method of Larhiri and Nurnberg (Lahiri and Nurnberger, 1991) or using a PAXgene blood DNA extraction kit (PreAnalytix Inc.). Genotype was determined by PCR amplification and restriction digestion with MwoI followed by size determination of digestion products by agarose gel electrophoresis as previously described (Zabetian et al., 2001). All genotypes were scored by two raters who were blind to treatment status.

2.1. Participants, selection criteria, and recruitment

2.6. Sample size

Participants age 18–45 were eligible if they met criteria for current opioid dependence and cocaine abuse or dependence, as assessed by the Structured Clinical Interview for DSM-IV (American Psychiatric Association, 2000; Spitzer et al., 1992). Participants were excluded if currently physiologically dependent on alcohol; using metronidazole or clotrimazole; experiencing significant cardiovascular, renal, hepatic or neurologic illness or had liver enzymes (alkaline phosphatase or alanine transaminase) greater than three times the upper limit of normal; dangerous to themselves or others; psychotic; or considered at risk for suicide or violence. Because of the potential cardiac complications in disulfiram-treated patients who use cocaine and alcohol, participants were also excluded if they had any of the following cardiac risk factors: first degree family member with a history of myocardial infarction prior to age 60, a past history of myocardial infarction, hypertension (systolic blood pressure > 140 or diastolic blood pressure > 90), or EKG evidence of myocardial infarction or ischemia. Women were included if they agreed to adequate contraception and to monthly pregnancy testing. Fig. 1 (CONSORT Diagram) shows participant flow through the phases of the study; a total of 177

We planned to enroll 90 subjects in each treatment condition in order to have sufficient power (0.80) to detect low- to moderate-sized effects, as found in prior studies (Carroll et al., 1998; George et al., 2000; Petrakis et al., 2000), assuming a type I error of 0.05 (Cohen, 1988). Because of the population distribution of the DBH genotype, we anticipated that the sample size would be sufficient to explore but have low power to test definitively potential differences associated with genotype in response to disulfiram.

2.5. Genotyping

2.7. Statistical analysis The primary outcomes, defined a priori, were frequency (the number of days per week) of cocaine use and the number of cocaine-negative urine tests in successive two-week intervals, and the maximum consecutive weeks of abstinence from cocaine, documented by urine toxicology testing. Secondary outcome measures included frequency (the number of days per week) of opioid use and the number of opioid-negative urine tests in successive two-week intervals, and the maximum

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Enrollment

Screened for eligibility (n=799)

Excluded (n= 590): Did not complete evaluation (n=271) Did not meet eligibility criteria (n=319) Enrolled (n=209)

Did not complete Bup induction (n=32)

Randomized (n=177)

Allocation Allocated to Buprenorphine (n=91 )

Allocated to Placebo (n=86)

Received allocated intervention (n=91)

Received allocated intervention (n=86 )

Did not receive allocated intervention (n=0 )

Did not receive allocated intervention (n= 0)

Follow-Up Discontinued intervention (n=48):

Discontinued intervention (n=37):

Incarcerated (n=3), Medical discharge (n=6), Stopped voluntarily (n=39)

Incarcerated (n=3), Medical discharge (n=3), Stopped voluntarily (n=31)

Analysis Analysed (n=91) Excluded from analysis (n=0)

Analysed (n=86) Excluded from analysis (n=0)

Fig. 1. Consort diagram. Figure shows the patient flow in the study.

consecutive weeks abstinent from illicit opioids, documented by urine toxicology testing. Data analyses, planned a priori, were based on an intention-to-treat sample of all randomized participants (N = 177) and also included plans for analyzing the subset of participants tested for DBH genotype (N = 155). Pre-randomization characteristics of study groups were compared using the Chi-square for categorical data and analysis of variance procedures (t-tests, ANOVA) for continuous variables. Treatment retention of study participants was evaluated using the Kaplan–Meier product limit method and the log rank test. Changes in frequency of cocaine use and the number of cocaine-negative urine tests during treatment were evaluated using a MIXED Models procedure in SPSS Version 15 with the effects of disulfiram vs. placebo as a between group factor and time (successive two-week intervals following randomization) as a repeated within subject factor, and the frequency of cocaine use during the induction as a covariate term. Frequency of cocaine use and number of cocaine-negative urine tests were aggregated into two-week intervals to create relatively continuous measures suitable for use with the Mixed Models procedure. The maximum number of consecutive weeks of abstinence from cocaine was computed for each participant based on the longest sequence of consecutive cocaine-negative urine tests, with missing urine tests considered as positive. The between group difference in the mean maximum consecutive weeks of abstinence was evaluated using the t-test. For comparison with other studies, we also compared the proportions of participants in the disulfiram and placebo groups achieving 3 or more consecutive weeks of cocaine abstinence, using chi square. Analyses of illicit opioid use outcomes followed a similar data analytic approach, and the relationship between cocaine and illicit opioid use during treatment was also examined using the Pearson correlation coefficient. Similar analyses were performed on the sample of study participants with available genetic data. Specifically, to explore whether genotype influenced response to disulfiram, we included genotype (T-allele carrier or CC-homozygous) as an additional factor in the Mixed Models procedure, and we also classified participants into four groups based on genotype and medication (i.e., T-allele carrier/disulfiram, T-allele carrier/placebo, CC-homozygous/disulfiram, CC-homozygous placebo) and used a Mixed Models procedure to evaluate whether the classification was associated with statistically significant effects on the primary outcome measures.

The small number of TT homozygotes in the general population (approximately 4%) and in the study population (6%) precludes separate evaluation for these subjects.

3. Results 3.1. Participant characteristics The two study groups did not differ significantly on any demographic characteristics or baseline measures of cocaine or opioid use severity (Table 1). 3.2. Retention Treatment retention did not differ between disulfiram- and placebo-treated subjects (mean (SE) 8.9 (0.4) vs. 9.1 (0.4) weeks, respectively; p = .55). Early termination was primarily voluntary Table 1 Baseline characteristics of study participants by medication group. N = 177

Placebo (n = 86)

Disulfiram (n = 91)

Age % Females % White Years of opiate use Years of cocaine use Days of opiate use in the past 30 Days of cocaine use in the past 30 % IV drug use

31.3 (6.8) 27/86 (31.4%) 56/86 (65.1%) 7.2 (5.5) 8.1 (5.1) 26.1 (6.2) 12.4 (8.8) 36.6%

31.7 (7.3) 23/91 (25.3%) 67/91 (73.6%) 7.6 (6.5) 9.3 (6.8) 24.8 (7.5) 11.9 (8.4) 32.1%

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(63 participants stopped coming for medications and one participant transferred to methadone maintenance) but also included incarceration (6 participants) and medical reasons (9 participants, including 1 who became pregnant, 7 who had persistent elevations of liver enzymes exceeding 3 times the upper limit of normal, and one following an episode of tachycardia and chest pain).

statistically different between the two groups. The proportion of opiate-negative urine tests was significantly correlated with the proportion of cocaine-negative tests during treatment (r = 0.523, p < .001).

3.3. Disulfiram effects on cocaine use

In the sub-sample for whom we had genotype data (N = 155), we found a statistically significant effect of medication on the frequency of cocaine use (F(1,137.1) = 4.92, p < .05), with the mean (SE) days of cocaine use per week during treatment of 0.61 (0.12) days in the disulfiram group and 1.0 (0.13) days in the placebo group. There were no significant main effects of genotype (F(1,137), p = .59) or time (F(5,102.3) = 1.68, p = .15) or significant two-way or three way interactions. There were significant differences associated with the four group classification of participants on the frequency of cocaine use (F(3,584.2 = 7.78, p < .05), with self-reported days of cocaine use lowest in T-allele carriers treated with disulfiram (see Fig. 3); the effects of time (F(5,179) = 1.18, p = .32) and of the interaction between the four group classification and time (F(15,193.9) = 0.33, p = .99) were not significant. The number of cocaine-negative urine tests (F(3,154) = 0.58, p = .63) and the maximum consecutive weeks of cocaine abstinence (F(3,154) = 0.72, p = .54) did not differ significantly among the four groups.

In the intention-to-treat sample (N = 177), disulfiram was associated with a significantly lower frequency of self-reported cocaine use during the clinical trial, as indicated by a significant main effect of medication (F(1,157.4) = 3.94, p < .05), with the mean (SE) days of cocaine use per week during treatment of 0.66 (0.12) days in the disulfiram group and 0.99 (0.12) days in the placebo group (see Fig. 2). The effects of time in treatment (F(5,116.5) = 2.26, p = .054) and of the interaction between medication and treatment time (F(5, 116.5) = 1.67, p = .14) were not significant. The difference in the mean (SD) number of cocaine negative urine samples (10.0 (11.4) and 10.7 (11.5) in the placebo and disulfiram groups respectively) was not significantly affected by medication (F(1,164.3) = 0.80, p = .37), time in treatment (F(5,121.5) = 0.14, p = .98), or the interaction between medication and treatment time (F(5,121.5) = 0.71, p = .62). Medication effects on the maximum number of consecutive weeks of cocaine abstinence based on urine toxicology results (1.8 (2.3) and 1.5 (1.6) weeks in the placebo and disulfiram groups respectively) were not statistically significant (t(175) = 0.81, p = .42); 16/91 (18%) in the disulfiram group and 18/86 (21%) in the placebo group achieved 3 or more weeks of abstinence (Chi-square(1) = 0.319, p = 0.57). 3.4. Effects on illicit opioid use There were no significant differences between disulfiram and placebo on the frequency of illicit opioid use (F(1,121.6) = 0.66, p = .42), with the mean (SE) days of illicit opioid use per week during treatment of 0.89 (0.15) days in the disulfiram group and 0.71 (0.15) days in the placebo group. The number of opioid-negative urine tests (t(175) = 1.38, p = .17) and maximum consecutive weeks of abstinence from illicit opioids (t(175) = 1.5, p = .14) were also not

Fig. 2. Disulfiram effects on frequency of cocaine use—Intention-to-treat sample (N = 177). Figure shows the mean days per week of cocaine use in each treatment group in the intention-to-treat sample (N = 177) during successive two-week time intervals from the two-week pre-randomization induction period until the end of week 12 of treatment with disulfiram 250 mg daily or placebo. The numbers of participants in each treatment group evaluated during the successive time periods are shown below the X-axis in the figure.

3.5. Exploration of pharmacogenetic effects

3.6. Interactions with alcohol and adverse events Relatively few subjects reported any alcohol consumption during the study (33 subjects, including 15 placebo-treated subjects and 18 disulfiram-treated subjects; no subject tested positive for alcohol at any visit), and alcohol use did not differ for placebo compared to disulfiram-treated subjects. Adverse events involving panic, anxiety or paranoia were reported by 13 subjects, including 8% (7/83) of disulfiram-treated and 7% (6/82) of placebo-treated subjects. During weekly ratings of medical or psychiatric symptoms, 23 subjects reported experiencing cocaine-related symptoms of anxiety (e.g., trembling) that were usually rated as mild; 13.3% (11/83) of disulfiram-treated and 14.6% (12/82) of placebo-treated

Fig. 3. Disulfiram effects for T allele carriers and CC homozygous subjects (N = 155). Figure shows the mean days per week of cocaine use during successive two-week time intervals from the two-week pre-randomization induction period until the end of week 12 of treatment for CC-homozygous participants treated with disulfiram 250 mg daily (n = 40) or placebo (n = 44) and for T-allele carriers treated with disulfiram 250 mg daily (n = 40) or placebo (n = 29). The numbers of participants in each treatment group evaluated during the successive time periods are shown below the X-axis in the figure.

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subjects reported these symptoms (2 = 0.07; NS). Of the 7 participants discharged due to elevated liver enzymes, 5 were treated with disulfiram and 2 with placebo. 4. Discussion The study findings provide limited support for the potential efficacy of disulfiram for reducing cocaine use: Consistent with several prior clinical trials (Carroll et al., 2004, 1998; George et al., 2000; Oliveto et al., 2011; Petrakis et al., 2000), disulfiram 250 mg daily was associated with significantly greater reductions in the frequency of self-reported cocaine use. The magnitude and clinical significance of the effects on cocaine use frequency were modest, however, and the differences with regard to urine test results or sustained abstinence were not significant. While the overall frequency of self-reported cocaine use during the study was low, very few participants in either treatment group achieved significant periods of cocaine abstinence. As with earlier studies, any effects of disulfiram on cocaine use were independent of disulfiram effects on alcohol use, since alcohol use was low and comparable in the two treatment groups. In the exploratory analyses of whether DBH genotype influences response to disulfiram, in a four-group comparison, the study found that the response to disulfiram was greatest for T-allele carriers at the −1021C→T SNP. Despite starting with similar frequencies of cocaine use during buprenorphine induction and stabilization, placebo-treated T-allele carriers had the highest frequency of cocaine use and disulfiram-treated T-allele carriers had the lowest frequency during treatment, while there were no significant differences between CC-homozygous individuals treated with active or placebo disulfiram. The finding of reductions in cocaine use frequency with disulfiram 250 mg only among T-allele carriers may suggest that the disulfiram dose was sufficient to lower D␤H to levels associated with a clinical response in T-allele carriers, who have lower baseline D␤H activity, but not in CC-homozygous individuals, who have higher baseline D␤H (and thus might need a higher disulfiram dose to obtain a response). This finding should be interpreted cautiously, however, since the study did not find a significant pharmacogenetic interaction when DBH genotype was included as an additional factor in the Mixed Models analysis (indicating that the interaction accounts for relatively little of the variance in the results), and there were no significant differences among the four groups with regard to the number of cocaine-negative urine tests or maximum consecutive weeks abstinent during treatment. The findings that T-allele carriers but not CC-homozygous individuals reduced the frequency of cocaine use when treated with disulfiram are also discrepant with the results of a recent study conducted during methadone maintenance treatment, which found significant differences in the proportion of cocaine-positive urine tests only between CC-homozygous participants treated with disulfiram 250 mg and placebo but not among T-allele carriers (Kosten et al., 2012). The discrepant findings may be due to differences in the opioid agonist maintenance medication (e.g., unlike methadone, buprenorphine is also a kappa antagonist), study population, or primary outcome measure and point to the importance of additional research to delineate more clearly the potential differential effects of disulfiram on cocaine use depending on DBH genotype. The mechanism by which disulfiram may affect cocaine use remains speculative. Although some studies suggest that disulfiram may exacerbate dysphoric reactions to cocaine (Hameedi et al., 1995; McCance-Katz et al., 1998a,b; Mutschler et al., 2009; Cubells et al., 2000; Schank et al., 2006; Weinshenker, 2010), in this study there was no indication that disulfiram increased aversive effects of cocaine: Very few participants reported cocaineinduced anxiety or paranoia; the severity of anxiety symptoms was generally rated as mild; the incidence and severity of these

symptoms did not differ between disulfiram- and placebo-treated participants. Other possible mechanisms mediated through inhibition of D␤H include reducing the rewarding properties of cocaine or ameliorating the persistent effects of cocaine on dopaminergic or noradrenergic functioning, mood (hedonic dysregulation) and neuropsychological functioning (Hameedi et al., 1995; Kalayasiri et al., 2007; McCance-Katz et al., 1998a,b; Schank et al., 2008, 2006; Sofuoglu et al., 2008; Weinshenker, 2010) or attenuating drug-primed or stress-induced relapse (Schroeder et al., 2010; Weinshenker, 2010). Disulfiram effects on cocaine use might also result from mechanisms other than inhibition of D␤H, such as inhibition of aldehyde dehydrogenase-2, as suggested by the findings of preclinical research in rats that ALDH-2 suppresses cocaine self-administration and cocaine- or cue-induced reinstatement of cocaine-seeking behavior (Weinshenker, 2010; Yao et al., 2010). Several limitations of the study should be noted. First, the study was conducted with opioid dependent participants receiving buprenorphine maintenance treatment, and the stringent eligibility criteria adopted to ensure the safety of study participants also limits the generalizability of the study results. Additionally, many potential subjects did not want treatment with disulfiram and did not complete the evaluation for study entry. Medication adherence in this study was good–medications were administered under direct observation six days per week–and retention in treatment was adequate, especially considering that cocaine use is negatively correlated with treatment retention (Haddad et al., 2013), and within the lower range of other studies of buprenorphine maintenance treatment (Fiellin et al., 2008, 2006; Mattick et al., 2003), but attrition and missing data due to attrition create problems with the data analysis that can only be partially addressed by the use of any data analytic procedure, including Mixed Models. Some participants reduced cocaine use during buprenorphine induction and stabilization, and had no or only occasional use during the study period. Cocaine use among participants in this study was significantly correlated (r = 0.52) with illicit opioid use, and initiation of buprenorphine maintenance treatment may have led to elimination or substantial reduction of cocaine use for some participants. Inclusion of these participants may have created a floor effect, decreasing the power of this study to detect significant medication effects. Finally, the evaluation of potential pharmacogenetic interactions was intended as an exploratory analysis, and the finding of a potential pharmacogenetic interaction should not be considered robust or definitive. In the exploratory analyses, we did not correct the significance level to account for multiple comparisons, and we did not find significant differences associated with the four genotype by medication groups with regard to the other primary outcome measures, nor did we find significant interactions between genotype and medication when genotype was included as an additional term in the statistical models. Additionally, genotyping was not performed prior to assignment to active disulfiram or placebo, resulting in some imbalance in the numbers of T-allele carriers assigned to disulfiram (n = 40) and placebo (n = 29). The relatively small number of participants within each genotype group assigned to each medication group reduces the power of the study to detect significant effects and also increases the possibility that findings from one small sample will be discrepant from findings from other small samples in other studies (Kosten et al., 2012). The study findings providing some limited support for the efficacy of disulfiram for reducing cocaine use during buprenorphine maintenance treatment and suggesting that disulfiram effects on cocaine use may result from inhibition of D␤H point to the importance of additional studies, with larger sample sizes adequately powered to detect potential pharmacogenetic interactions with disulfiram, and using a range of disulfiram doses, including doses above 250 mg daily. Safety concerns about disulfiram, which can cause fulminant hepatitis and neuropathies, including optic

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neuritis (Chick, 1999; Enghusen Poulsen et al., 1992), may also limit its use for treating cocaine use disorders, especially at higher doses, supporting the importance also of investigating other, more selective and potentially safer inhibitors of D␤H, including the selective D␤H inhibitor nepicastat, that might be effective for treating cocaine dependence and might also help delineate disulfiram’s mechanism of action. Role of Funding Source: Funding for this study was provided by grants from the National Institute on Drug Abuse (NIDA) (K24 DA000445 (R.S.S.), K05DA0454 (T.R.K.), K02-DA-016611 (T.P.G.) and K02 DA015766 (J.F.C.)). The NIDA had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. Contributors Authors Schottenfeld and George designed the study and wrote the protocol. Authors Kosten and Cubells contributed to the initial study design and protocol development. Authors Schottenfeld and Chawarski managed all aspects of the study during its implementation. Authors Cubells and Lappalainen developed the pharmacogenetic hypothesis and managed the DBH genotype testing. Author Chawarski undertook the statistical analysis. Author Schottenfeld wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript. Conflict of Interest Thomas Kosten has served as a consultant and speaker for Reckitt Benckiser for the last 3 years. Richard Schottenfeld has served as a consultant for AstraZeneca for the past year. At the time the study was conducted, Jaakko Lappalainen was a faculty member of the Department of Psychiatry, Yale University Medical School. Currently, he is Senior Director, Clinical Research, AstraZeneca. All other authors declare that they have no conflicts of interest. References American Psychiatric Association, 2000. Diagnostic and Statistical Manual of Mental Disorders DSM-IV-TR. American Psychiatric Publishing, Washington, DC. Arfken, C.L., Johanson, C.E., di Menza, S., Schuster, C.R., 2010. Expanding treatment capacity for opioid dependence with office-based treatment with buprenorphine: national surveys of physicians. J. Subst. Abuse Treat. 39, 96–104. Baker, J.R., Jatlow, P., McCance-Katz, E.F., 2007. Disulfiram effects on responses to intravenous cocaine administration. Drug Alcohol Depend. 87, 202–209. Bourdélat-Parks, B.N., Anderson, G.M., Donaldson, Z.R., Weiss, J.M., Bonsall, R.W., Emery, M.S., Liles, L.C., Weinshenker, D., 2005. Effects of dopamine ␤hydroxylase genotype and disulfiram inhibition on catecholamine homeostasis in mice. Psychophamacology 183, 72–80. Bux, D.A., Lamb, R.J., Iguchi, M.Y., 1995. Cocaine use and HIV risk behavior in methadone maintenance patients. Drug Alcohol Depend. 37, 29–35. Carroll, K., Ziedonis, D., O’Malley, S.S., McCance-Katz, E., et al., 1993. Pharmacologic interventions for alcohol- and cocaine-abusing individuals: a pilot study of disulfiram vs. naltrexone. Am. J. Addict. 2, 77–79. Carroll, K.M., Fenton, L.R., Ball, S.A., Nich, C., Frankforter, T.L., Shi, J., Rounsaville, B.J., 2004. Efficacy of disulfiram and cognitive behavior therapy in cocainedependent outpatients: a randomized placebo-controlled trial. Arch. Gen. Psychiatry 61, 264–272. Carroll, K.M., Nich, C., Ball, S.A., McCance, E., Rounsavile, B.J., 1998. Treatment of cocaine and alcohol dependence with psychotherapy and disulfiram. Addiction 93, 713–727. Chaisson, R.E., Bacchetti, P., Osmond, D., et al., 1989. Cocaine use and HIV infection in intravenous drug users in San Francisco. JAMA 261, 561–565. Chick, J., 1999. Safety issues concerning the use of disulfiram in treating alcohol dependence. Drug Safety 20, 427–435. Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, Hillsdale, NJ. Cubells, J.F., Kranzler, H.R., McCance-Katz, E., Anderson, G.M., Malison, R.T., Price, L.H., Gelernter, J., 2000. A haplotype at the DBH locus, associated with low plasma

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