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Original Investigation |

Naltrexone vs Placebo for the Treatment of Alcohol Dependence A Randomized Clinical Trial FREE

David W. Oslin, MD1,2; Shirley H. Leong, PhD2; Kevin G. Lynch, PhD1; Wade Berrettini, MD, PhD1; Charles P. O’Brien, MD, PhD1; Adam J. Gordon, MD, MPH3,4,5; Margaret Rukstalis, MD6
[+] Author Affiliations
1Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, Philadelphia
2Mental Illness Research, Education, and Clinical Center, Center of Excellence for Substance Abuse Treatment and Evaluation, Philadelphia Veterans Affairs Medical Center, Philadelphia, Pennsylvania
3Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
4Mental Illness Research, Education, and Clinical Center, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
5Center for Health Equity Research and Promotion, Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania
6Department of Psychiatry, Wake Forest University, Winston-Salem, North Carolina
JAMA Psychiatry. 2015;72(5):430-437. doi:10.1001/jamapsychiatry.2014.3053.
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Published online

Importance  Alcohol use disorder is one of the leading causes of disability worldwide. While effective pharmacological treatments exist, they are efficacious only in certain individuals, contributing to their limited use. Secondary analysis of clinical trial data suggests that a functional polymorphism (rs1799971, Asn40Asp) of the µ-opioid receptor gene (OPRM1) is associated with the risk of relapse to heavy drinking following treatment with the opioid antagonist naltrexone.

Objective  To prospectively examine whether rs1799971 is predictive of naltrexone treatment response.

Design, Setting, and Participants  We conducted a 12-week, double-blind, randomized clinical trial of naltrexone vs placebo in individuals with alcohol dependence (intent-to-treat analysis). Participants were randomly assigned to study treatment based on the presence of 1 or 2 copies of the Asp40 allele compared with those homozygous for the Asn40 allele (2 × 2 cell design). Recruitment occurred between January 2009 and September 2013. All participants were seen in an outpatient clinical setting. A convenience sample of participants (n = 221) was recruited from 5 sites. All participants met DSM-IV criteria for alcohol dependence, with no concurrent psychotic or manic symptoms, no use of concurrent psychotropic medications, and no current dependence on illicit substances.

Interventions  The study drug was naltrexone (50 mg) given once daily or corresponding placebo.

Main Outcomes and Measures  The primary study outcome measure was relapse to heavy drinking measured using the timeline follow-back method.

Results  There was no evidence of a genotype × treatment interaction on the primary outcome of heavy drinking (P = .32). In the Asn40 group, the observed effect of naltrexone was similar to that in previous trials (odds ratio, 0.69; 95% CI, 0.41-1.18; P = .17), with a very small naltrexone effect in the Asp40 group (odds ratio, 1.10; 95% CI, 0.52-2.31; P = .80), contrary to the pattern expected a priori. A significant reduction in heavy drinking occurred across all groups (P = .001). Other drinking outcomes, and all secondary outcomes, demonstrated similar time effects, with no genotype × treatment interaction.

Conclusions and Relevance  The results of this study do not support the hypothesis that the Asp40 allele moderates the response to naltrexone treatment. It is premature to use the Asn40Asp polymorphism as a biomarker to predict the response to naltrexone treatment of alcohol dependence.

Trial Registration  clinicaltrials.gov Identifier: NCT00831272

Figures in this Article

Alcohol dependence is one of the leading causes of disability worldwide.1 Over the last 2 decades, there have been dozens of randomized placebo-controlled trials of naltrexone for the treatment of alcohol dependence.2 Despite the better group response to naltrexone in clinical trials, significant variability exists in the response among individuals treated with naltrexone. Based on both preclinical research and promising clinical trial data, it has been hypothesized that the functional, nonsynonymous single-nucleotide polymorphism (SNP) of the µ-opioid receptor gene (A+118G, Asn40Asp, rs1799971) is a biomarker that predicts naltrexone treatment response.3,4

Retrospective analysis of clinical trial data showed that individuals with alcohol dependence and 1 or 2 copies of the Asp40 allele were significantly more likely not to relapse to heavy drinking with naltrexone treatment (73.9%) than individuals homozygous for the Asn40 allele (49.0%).5 In individuals receiving placebo, there was no association between genotype and treatment response. This finding was replicated in a retrospective review of data from the Combined Pharmacotherapies and Behavioral Interventions (COMBINE) Study.6 In that study, 87% of individuals assigned to medical management with naltrexone who had 1 or 2 copies of the Asp40 allele had a good treatment outcome compared with a 49% response among Asn40 allele homozygotes treated with naltrexone. However, other clinical studies711 have failed to demonstrate this pharmacogenetic effect. Human laboratory settings also suggest clinical relevance of the Asp40 allele among individuals exposed to alcohol, including higher rates of stimulation,12 which is blocked by naltrexone,13 and greater cue-induced craving.1416

While much of the literature supports the hypothesis that the Asp40 allele is a functional variant with clinical manifestations, there are important limitations to the existing treatment data that cast doubt on the use of this allele as a biomarker to predict naltrexone treatment response. In particular, the clinical studies to date have relied on secondary analysis of randomized clinical trials in which genotype was not available for all participants. Furthermore, while not a rare polymorphism, the Asp40 allele frequency in individuals of European ancestry is approximately 15%,17 limiting the number of individuals with the allele in most studies. Moreover, given the substantial diversity in allele frequencies among African American, Asian, and European populations, sampling strategies and randomization in prior studies would not have been designed to address this diversification.17

The aim of this study was to examine prospectively the interaction between the Asp40 allele and the response to treatment of alcohol dependence with naltrexone. We hypothesized that individuals exposed to naltrexone who carry at least 1 copy of the Asp40 allele would have the greatest response to treatment, while the other 3 treatment groups (Asp40/placebo, Asn40/naltrexone, and Asn40/placebo) would have an equal but poorer response to treatment. The primary outcome was defined as the presence of heavy drinking during each week of the trial.

Trial Design and Participants

The study was a 12-week, double-blind, randomized clinical trial of naltrexone vs placebo with stratification by genotype. Eligible participants had to be at least 18 years of age, meet DSM-IV criteria for alcohol dependence as assessed by a structured diagnostic interview,18 report a minimum mean of more than 21 standard drinks per week and 2 days per week of heavy drinking, and be of European or Asian descent. Before randomization, participants had to achieve at least 24 hours of self-reported abstinence. Individuals were not included if they had a current DSM-IV diagnosis of any psychoactive substance dependence other than alcohol or nicotine or provided a urine sample positive for the presence of cocaine or opioids. Individuals could not be taking psychotropic medications or have a current diagnosis of psychosis, mania, or posttraumatic stress disorder or be currently enrolled in an addiction treatment program. Other exclusion criteria included serious medical illness (eg, active hepatitis), elevations of alanine aminotransferase (upper limit, 45 U/L for men and 33 U/L for women) and aspartate aminotransferase greater than 5 times the upper limit of normal or elevation of bilirubin (upper limit, 1.2 mg/mL) of 1.3 times the upper limit of normal, and women who were pregnant, nursing, or not using a reliable method of contraception (to convert alanine aminotransferase level to microkatals per liter, multiply by 0.0167; to convert bilirubin level to micromoles per liter, multiply by 17.014).

Recruitment

A convenience sample of participants was recruited through advertisements in local media, referrals from physicians, or self-referrals. Recruitment occurred between January 2009 and September 2013. Participants were recruited from 5 sites, including Philadelphia, Pennsylvania (n = 151); Media, Pennsylvania (n = 20); the Philadelphia Veterans Affairs Medical Center (n = 26); the Veterans Affairs Pittsburgh Healthcare System (n = 16); and the Geisinger Medical Center (Danville, Pennsylvania) (n = 8). The study was reviewed and approved by the institutional review board at each of 5 sites. All participants provided written informed consent. The protocol manuscript is provided in Supplement 1.

Because the allele frequency for the Asp40 allele approximates 0.15 in European ancestry individuals, we oversampled participants with the risk allele. Genotyping was conducted at the time of informed consent and was reviewed by a nonblinded staff member who informed the study team of an individual’s eligibility but did not report the genotype results. The nonblinded staff member used a random procedure to select every other consenting participant who was homozygous for the Asn40 allele.

Interventions
Treatment With Naltrexone

Participants randomized to naltrexone received a dosage of 50 mg/d as recommended by the US Food and Drug Administration. All medication was distributed in blister packs that included 8 days of medication.

Medical Management

Medical management (MM) is a manualized psychosocial intervention that was designed for the multisite COMBINE Study.19 The goal of MM is to provide a basic, minimal form of clinical intervention supporting the use of effective pharmacotherapy and reduction in alcohol consumption. Sessions last approximately 30 minutes. The maximum number of sessions was 11. Session content included education about naltrexone, counseling on steps to reduce alcoholconsumption, and monitoring of safety (adverse events), treatment adherence (pill counts and visit attendance), and drinking status.

Before participation, each therapist was certified in the delivery of MM. Fidelity to treatment was monitored by reviewing a random set of session tapes, with no significant therapeutic drift detected. There were 14 MM therapists who participated in the trial.

Outcome Measures

Standard research assessments measured the amount of drinking, severity of alcohol problems, and level of psychosocial functioning. Trained technicians who were blinded to randomization assignment and not directly involved in the treatment of participants administered the assessments. The primary outcome measure was obtained using the timeline follow-back method to assess alcohol consumption.2022 The timeline follow-back method is a semistructured interview that uses a calendar format to record the quantity and frequency of drinking per day during a stated period. Drinking reports were recorded for the 60 days preceding enrollment and throughout the intervention period. The quantity of alcohol was recorded in standard alcohol drinks containing 14 g of alcohol (eg, a 12-oz beer, a 5-oz glass of wine, or a 1½-oz shot of spirits). Heavy drinking was defined as 5 or more drinks in a single day for men or 4 or more drinks in a single day for women.23,24 Secondary measures of outcome included subjective quality of life as measured by the Medical Outcomes Study 12-Item Short-Form Health Survey25 and alcohol craving as measured by the Penn Alcohol Craving Scale.26 Prestudy severity of problems related to drinking was measured by the Short Index of Problems.27

Medication adherence was measured using well-marked blister cards, pill counts, and participant interviews,28 while clinic visit attendance was tracked by the therapist. Potential adverse events were recorded by the therapist at each visit.

For genotyping, all genetic testing was done at the University of Pennsylvania. Genomic DNA was extracted from blood samples by standard methods.29 The A+118G SNP was genotyped using a TaqMan sample-to-SNP assay (C_8950074_1; Applied Biosystems). Sequencing-confirmed homozygous G DNA was used as a positive control, and sequencing-confirmed homozygous A DNA was used as a negative control. Genetic testing results were obtained before randomization and were used to confer eligibility and to stratify the randomization.

Sample Size

Based on the randomized sample of 221 and the observed dropout rates and within-participant correlation of 0.57, the study had 80% power to detect an interaction odds ratio of 3.72. Originally, the goal of the study was to randomize 150 participants with the Asp40 allele. With the same observed dropout and correlation, this would have yielded 80% power to detect an interaction odds ratio of 2.9.

Randomization

Participants were randomly allocated to the 2 treatment groups separately within each site and stratified by genotype (2 × 2 cell design). Blocked randomizations were used with a block size of 10 and PROC PLAN (SAS, version 9.3; SAS Institute Inc), created before the start of the study.

Statistical Analysis

Baseline characteristics of the 4 genotypes by medication group were compared using χ2 test for categorical variables and Wilcoxon rank sum test for continuous variables. Repeated weekly measures of drinking outcomes were compared using generalized estimating equation (GEE) models.30 In all GEE models, the explanatory variables of primary interest comprised binary indicators for intervention group, genotype, and their interaction; a linear trend for time; and terms for interactions involving time and the group and genotype factors. In addition, all models included a factor for site and the pretreatment version of the response as a covariate. The significance of the interaction terms was evaluated based on P values from score tests in the GEE models. A compound symmetry structure was used for the working correlation matrix, and empirical (robust) standard errors were used. The presence or absence of heavy drinking in a week was modeled using a GEE logistic regression model. The number of days of heavy drinking in a week was modeled as a binomial outcome (range, 0 to the number of days reported on for that week) using GEE binomial regression models, with the number of heavy days out of available days in each week as the event or trial response. The presence or absence of any drinking and the number of drinking days were analyzed in the same way. Secondary outcomes were also compared using GEE models.

Inverse probability–weighted GEE models and pattern-mixture models comparing completers and noncompleters were used to assess the sensitivity of the primary timeline follow-back method models to missing data.31,32 A set of non-intent-to-treat models was used to assess the effects of nonadherence on the analyses.33

Randomization and Baseline Characteristics

There were 480 individuals who consented to participate in the study, of whom 221 were randomized (Figure 1). Most participants who were not randomized were excluded through the oversampling procedure. No differences were observed in sex, age, prestudy rates of heavy drinking, or prestudy percentage days of drinking between individuals who were randomized and Asn40 homozygotes who were not randomly selected to participate (P > .06). Recruitment was ended before reaching the specified sample size. Recruitment proceeded slower than anticipated, and the allele frequency among the participants was lower than anticipated. The observed allele frequency in those who consented was 12.7% (ie, 24.8% of screened individuals had at least 1 copy of the Asp40 allele).

Place holder to copy figure label and caption
Figure 1.
Consolidated Standards of Reporting Trials Diagram

Adherence is defined as taking at least 80% of medication. TLFB indicates timeline follow-back.

Graphic Jump Location

For the randomized sample, the mean (SD) age of the participants was 48.5 (12.6) years, with most being male (85.9%) and of white race (98.2%). Clinical characteristics before treatment indicate that participants drank on a mean (SD) of 82.0% (20.7%) of days preceding enrollment and drank heavily on a mean (SD) of 69.6% (27.8%) of days. With regard to alcohol-related problems, the mean (SD) Short Index of Problems score was 17.7 (10.4). Overall, there were only minor differences in the baseline variables across the 4 study groups (Table) (additional prestudy characteristics are provided in the eResults in Supplement 2).

Drinking Outcome Measures

For the primary outcome of heavy drinking, a significant time-dependent decrease in heavy drinking during the trial was observed for all groups (GEE score test χ21 = 12.18, P = .001), with no significant group × time interactions. Percentage days of heavy drinking at baseline was a significant predictor (GEE score test χ21 = 7.38, P = .007), with higher rates of heavy drinking at baseline associated with higher probability of heavy drinking during the trial. The site variable was not significant (GEE score test χ21 = 0.40, P = .53). The genotype × treatment interaction was not significant (GEE score test χ21 = 0.98, P = .32) (Figure 2).

Place holder to copy figure label and caption
Figure 2.
The Proportion of Participants With Any Heavy Drinking Within a Given Treatment Week Separated by Genotype and Treatment Group

There were no significant differences in outcomes among the 4 groups when adjusting for site and baseline rates of heavy drinking.

Graphic Jump Location

The model containing the genotype × treatment interaction provides separate estimates of the medication odds ratio for heavy drinking for the Asn40 and Asp40 strata. In the Asn40 stratum, the odds of heavy drinking in the naltrexone group was estimated to be 0.69 (95% CI, 0.41-1.18) times the corresponding odds in the placebo group (P = .17). In the Asp40 stratum, the odds of heavy drinking in the naltrexone group was estimated to be 1.10 (95% CI, 0.52-2.31) times the corresponding odds in the placebo group (P = .80).

Analyses of the numbers of heavy drinking days per week, the presence or absence of any drinking, and the numbers of drinking days per week showed similar results, with genotype × treatment interaction score statistics of 1.86 (P = .17), 1.60 (P = .21), and 0.31 (P = .58), respectively (eFigure 1 and eFigure 2 in Supplement 2). The survival analysis to the time of first heavy drinking was also not significant (eFigure 3 in Supplement 2). Weighted GEE models, pattern-mixture models, and analysis of secondary outcomes showed similar results (eFigure 4 and eFigure 5 in Supplement 2).

Treatment Adherence

The group proportions of participants adhering for at least 80% of all 12 weeks of treatment days were 66.7% (Asn40/placebo), 72.6% (Asn40/naltrexone), 79.6% (Asp40/placebo), and 50.0% (Asp40/naltrexone), with a significant genotype × treatment interaction (GEE score test χ21 = 7.28, P = .007). Adherence rates in the Asp40/naltrexone group were significantly lower than those in the Asn40/naltrexone group (P = .02). Analysis of participants only adherent and analysis up to the time of dropout were also nonsignificant (P = .23 and P = .12, respectively), and estimates of naltrexone effects in the genotype groups were similar to those for the intent-to-treat analyses above (eResults in Supplement 2). The survival analysis to the time of discontinuation was not significantly different between groups (eFigure 6 in Supplement 2). Exploratory analyses demonstrated that the first occurrence of heavy drinking occurred before any evidence of nonadherence to treatment because 131 participants out of 155 with heavy drinking outcomes had perfect adherence before their heavy drinking. Participants attended a mean (SD) of 8.5 (2.9) MM sessions, with no significant differences in the number attended per group (GEE score test χ23 = 1.93, P = .59).

Adverse Effects

Five participants experienced a serious adverse event, all leading to early termination of treatment. Three participants (1 Asn40/placebo, 1 Asn40/naltrexone, and 1 Asp40/placebo) relapsed sufficiently to require inpatient detoxification. A fourth participant (Asn40/placebo) was hospitalized for a suicide attempt, and the fifth participant (Asp40/placebo) was hospitalized for diabetes mellitus. Adverse events rated as severe were infrequent and were unrelated to group assignment, and only 2 led to discontinuation. The frequencies of severe adverse events were 3 participants with gastrointestinal complaints, 3 participants with worsening pain, 2 participants with nausea, 2 participants with change in libido,1 participant with headache, and 1 participant with disruption of sleep. Additional findings on the occurrence of adverse events are included in the eResults in Supplement 2.

The results from this prospective randomized trial failed to demonstrate a moderating effect of the Asn40Asp SNP in OPRM1 (OMIM 600018) on naltrexone treatment response among individuals with alcohol dependence. We oversampled participants with the purported risk allele and stratified the randomization based on genotype. While there was not an overall significant effect of naltrexone in the entire sample, the reduction in heavy drinking in the Asn40/naltrexone group is comparable to the reductions in heavy drinking seen in most studies of naltrexone (odds ratio, 0.69).34 In the Asp40 allele group, the effect of naltrexone was very small and opposite to the predicted direction. Therefore, while the study did not achieve the intended sample size due to early termination of the trial, it is highly unlikely that a larger sample would have resulted in the demonstration of the expected moderating effect of the Asp40 allele.

There were significantly more individuals in the Asp40/naltrexone group who did not adhere to a full course of treatment. Analysis of completers and those adherent and examination of the temporal relationship between nonadherence and heavy drinking were all consistent with the main analysis and do not suggest that the differential adherence affects the interpretation of the results. The finding that heavy drinking occurs before nonadherence is consistent with findings from the COMBINE Study.35 While serious adverse events were uncommon, the Asp40/naltrexone group reported a higher frequency of adverse events, which may have contributed to higher rates of discontinuation, although that association was not apparent. Therefore, it is unclear what led to a higher dropout rate and what the implications are for this observation. While not significant, the results of the COMBINE Study6 also showed the lowest adherence in the Asp40/naltrexone group.

These results of this prospective trial appear to differ from previous human laboratory research and retrospective analysis of clinical trials.5,6,1216 However, almost all of the human laboratory studies were conducted in social drinkers without alcohol dependence and were of relatively small size, which are prone to greater error rates in interpreting effect size.36 As for the promising clinical trial data, all prior studies have been retrospective reanalyses of data, with one large study6 and smaller studies6,7 demonstrating a moderating effect of the SNP on naltrexone response but with other studies10,11 showing no moderating effect of the Asp40 allele. Some of the inconsistencies could be related to differences in design such as not genotyping all participants and variation in methods for analyzing noncompliance. The COMBINE Study6 only found a pharmacogenetic interaction with heavy drinking in weeks 12 through 16 and not earlier; therefore, the duration of treatment may affect the results. Unfortunately, this pattern of having very promising observational data not replicated in prospective clinical trials is not atypical for the pharmacogenetic field. To date, promising or even well-conceptualized pharmacogenetic findings have rarely influenced clinical practice. For example, despite clear evidence for differences in metabolism, genetic testing does not improve the clinical use of warfarin sodium.3739

The present trial was specifically designed to study the possible moderating effects of the Asp40 allele and was not powered to test potential moderators of this effect. As such, there were major differences from previous efficacy studies6,7,11 of naltrexone. The oversampling of the Asp40 allele substantially decreased the number of Asn40 homozygous participants. The exclusion of African Americans, while scientifically justified by the low Asn40 allele frequency, is also significantly different from other trials. Finally, many trials have used 100 mg/d of naltrexone, while this study used 50 mg/d as approved by the Food and Drug Administration. It is possible that 100 mg/d could be more effective through κ- or Δ-antagonism. In contrast, the design of the trial was reviewed by the Food and Drug Administration before the start of the study and was considered to be methodologically sound. Moreover, there was a high degree of fidelity to the protocol, with a small degree of missing data and no evidence of incorrect genotyping or errors in randomization (eAppendix in Supplement 2).

Despite the results of this trial, pharmacogenetics continues to hold promise as a way to improve the targeting of medications to improve treatment response. Linking genetics to such complex disease states as alcohol use disorders is not simple. Indeed, recent literature suggests that complex genetic interactions may have important roles in understanding treatment outcomes.40,41 These prospective results are important in having the field pause and evaluate the methods of pharmacogenetic trials and application of genetics to predict treatment response in patients with alcohol use disorder.

Submitted for Publication: May 8, 2014; final revision received December 1, 2014; accepted December 2, 2014.

Corresponding Author: David W. Oslin, MD, Department of Psychiatry, Perelman School of Medicine at the University of Pennsylvania, 3900 Chestnut St, Philadelphia, PA 19104 (oslin@upenn.edu).

Published Online: March 11, 2015. doi:10.1001/jamapsychiatry.2014.3053.

Author Contributions: Drs Oslin and Lynch had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Oslin, Lynch, Berrettini, O’Brien.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Oslin, Lynch.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Lynch.

Obtained funding: Oslin.

Conflict of Interest Disclosures: Dr O’Brien reported providing consultation to Alkermes PLC. No other disclosures were reported.

Funding/Support: This study was supported in part by grant AA017164 from the National Institute on Alcohol Abuse and Alcoholism and by the Veterans Integrated Service Network 4 Mental Illness Research, Education, and Clinical Center.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: Henry Kranzler, MD (Perelman School of Medicine at the University of Pennsylvania) contributed to preparation of the manuscript and interpretation of the results of the trial. No compensation was provided.

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Ware  J  Jr, Kosinski  M, Keller  SD.  A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220-233.
PubMed   |  Link to Article
Flannery  BA, Volpicelli  JR, Pettinati  HM.  Psychometric properties of the Penn Alcohol Craving Scale. Alcohol Clin Exp Res. 1999;23(8):1289-1295.
PubMed   |  Link to Article
Alterman  AI, Cacciola  JS, Ivey  MA, Habing  B, Lynch  KG.  Reliability and validity of the alcohol Short Index of Problems and a newly constructed drug Short Index of Problems. J Stud Alcohol Drugs. 2009;70(2):304-307.
PubMed   |  Link to Article
Pettinati  HM, Volpicelli  JR, Pierce  JD  Jr, O’Brien  CP.  Improving naltrexone response: an intervention for medical practitioners to enhance medication compliance in alcohol dependent patients. J Addict Dis. 2000;19(1):71-83.
PubMed   |  Link to Article
Lahiri  DK, Schnabel  B.  DNA isolation by a rapid method from human blood samples: effects of MgCl2, EDTA, storage time, and temperature on DNA yield and quality. Biochem Genet. 1993;31(7-8):321-328.
PubMed   |  Link to Article
Diggle  P, Heagerty  P, Liang  KY, Zeger  S. Analysis of Longitudinal Data. 2nd ed. New York, NY: Oxford University Press Inc; 2002.
Molenberghs  G, Verbeke  G. Models for Discrete Longitudinal Data. New York, NY: Springer; 2006.
Verbeke  G, Molenberghs  G. Linear Mixed Models for Longitudinal Data. New York, NY: Springer; 2000.
Ten Have  TR, Normand  SL, Marcus  SM, Brown  CH, Lavori  P, Duan  N.  Intent-to-treat vs. non–intent-to-treat analyses under treatment non-adherence in mental health randomized trials. Psychiatr Ann. 2008;38(12):772-783.
PubMed   |  Link to Article
Pettinati  HM, O’Brien  CP, Rabinowitz  AR,  et al.  The status of naltrexone in the treatment of alcohol dependence: specific effects on heavy drinking. J Clin Psychopharmacol. 2006;26(6):610-625.
PubMed   |  Link to Article
Stout  RL, Braciszewski  JM, Subbaraman  MS, Kranzler  HR, O’Malley  SS, Falk  D; ACTIVE Group.  What happens when people discontinue taking medications? lessons from COMBINE. Addiction. 2014;109(12):2044-2052.
PubMed   |  Link to Article
Leon  AC, Davis  LL, Kraemer  HC.  The role and interpretation of pilot studies in clinical research. J Psychiatr Res. 2011;45(5):626-629.
PubMed   |  Link to Article
Kimmel  SE, French  B, Kasner  SE,  et al; COAG Investigators.  A pharmacogenetic versus a clinical algorithm for warfarin dosing. N Engl J Med. 2013;369(24):2283-2293.
PubMed   |  Link to Article
Jonas  DE, Evans  JP, McLeod  HL,  et al.  Impact of genotype-guided dosing on anticoagulation visits for adults starting warfarin: a randomized controlled trial. Pharmacogenomics. 2013;14(13):1593-1603.
PubMed   |  Link to Article
Stergiopoulos  K, Brown  DL.  Genotype-guided vs clinical dosing of warfarin and its analogues: meta-analysis of randomized clinical trials. JAMA Intern Med. 2014;174(8):1330-1338.
PubMed   |  Link to Article
Schacht  JP, Anton  RF, Voronin  KE,  et al.  Interacting effects of naltrexone and OPRM1 and DAT1 variation on the neural response to alcohol cues. Neuropsychopharmacology. 2013;38(3):414-422.
PubMed   |  Link to Article
Ray  LA, Bujarski  S, Squeglia  LM, Ashenhurst  JR, Anton  RF.  Interactive effects of OPRM1 and DAT1 genetic variation on subjective responses to alcohol. Alcohol Alcohol. 2014;49(3):261-270.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Consolidated Standards of Reporting Trials Diagram

Adherence is defined as taking at least 80% of medication. TLFB indicates timeline follow-back.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
The Proportion of Participants With Any Heavy Drinking Within a Given Treatment Week Separated by Genotype and Treatment Group

There were no significant differences in outcomes among the 4 groups when adjusting for site and baseline rates of heavy drinking.

Graphic Jump Location

Tables

References

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PubMed   |  Link to Article
Ware  J  Jr, Kosinski  M, Keller  SD.  A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity. Med Care. 1996;34(3):220-233.
PubMed   |  Link to Article
Flannery  BA, Volpicelli  JR, Pettinati  HM.  Psychometric properties of the Penn Alcohol Craving Scale. Alcohol Clin Exp Res. 1999;23(8):1289-1295.
PubMed   |  Link to Article
Alterman  AI, Cacciola  JS, Ivey  MA, Habing  B, Lynch  KG.  Reliability and validity of the alcohol Short Index of Problems and a newly constructed drug Short Index of Problems. J Stud Alcohol Drugs. 2009;70(2):304-307.
PubMed   |  Link to Article
Pettinati  HM, Volpicelli  JR, Pierce  JD  Jr, O’Brien  CP.  Improving naltrexone response: an intervention for medical practitioners to enhance medication compliance in alcohol dependent patients. J Addict Dis. 2000;19(1):71-83.
PubMed   |  Link to Article
Lahiri  DK, Schnabel  B.  DNA isolation by a rapid method from human blood samples: effects of MgCl2, EDTA, storage time, and temperature on DNA yield and quality. Biochem Genet. 1993;31(7-8):321-328.
PubMed   |  Link to Article
Diggle  P, Heagerty  P, Liang  KY, Zeger  S. Analysis of Longitudinal Data. 2nd ed. New York, NY: Oxford University Press Inc; 2002.
Molenberghs  G, Verbeke  G. Models for Discrete Longitudinal Data. New York, NY: Springer; 2006.
Verbeke  G, Molenberghs  G. Linear Mixed Models for Longitudinal Data. New York, NY: Springer; 2000.
Ten Have  TR, Normand  SL, Marcus  SM, Brown  CH, Lavori  P, Duan  N.  Intent-to-treat vs. non–intent-to-treat analyses under treatment non-adherence in mental health randomized trials. Psychiatr Ann. 2008;38(12):772-783.
PubMed   |  Link to Article
Pettinati  HM, O’Brien  CP, Rabinowitz  AR,  et al.  The status of naltrexone in the treatment of alcohol dependence: specific effects on heavy drinking. J Clin Psychopharmacol. 2006;26(6):610-625.
PubMed   |  Link to Article
Stout  RL, Braciszewski  JM, Subbaraman  MS, Kranzler  HR, O’Malley  SS, Falk  D; ACTIVE Group.  What happens when people discontinue taking medications? lessons from COMBINE. Addiction. 2014;109(12):2044-2052.
PubMed   |  Link to Article
Leon  AC, Davis  LL, Kraemer  HC.  The role and interpretation of pilot studies in clinical research. J Psychiatr Res. 2011;45(5):626-629.
PubMed   |  Link to Article
Kimmel  SE, French  B, Kasner  SE,  et al; COAG Investigators.  A pharmacogenetic versus a clinical algorithm for warfarin dosing. N Engl J Med. 2013;369(24):2283-2293.
PubMed   |  Link to Article
Jonas  DE, Evans  JP, McLeod  HL,  et al.  Impact of genotype-guided dosing on anticoagulation visits for adults starting warfarin: a randomized controlled trial. Pharmacogenomics. 2013;14(13):1593-1603.
PubMed   |  Link to Article
Stergiopoulos  K, Brown  DL.  Genotype-guided vs clinical dosing of warfarin and its analogues: meta-analysis of randomized clinical trials. JAMA Intern Med. 2014;174(8):1330-1338.
PubMed   |  Link to Article
Schacht  JP, Anton  RF, Voronin  KE,  et al.  Interacting effects of naltrexone and OPRM1 and DAT1 variation on the neural response to alcohol cues. Neuropsychopharmacology. 2013;38(3):414-422.
PubMed   |  Link to Article
Ray  LA, Bujarski  S, Squeglia  LM, Ashenhurst  JR, Anton  RF.  Interactive effects of OPRM1 and DAT1 genetic variation on subjective responses to alcohol. Alcohol Alcohol. 2014;49(3):261-270.
PubMed   |  Link to Article

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Multimedia

Supplement 1.

Trial protocol

Supplemental Content
Supplement 2.

eResults. Supplemental Results

eFigure 1. Percent Days of Any Drinking During the Course of Treatment

eFigure 2. Drinks per Drinking Day During the Course of Treatment

eFigure 3. Survival Analysis to the First Heavy Drinking Day

eFigure 4. Change in the Mental Health Component Score (MHC) From Pretreatment to Posttreatment

eFigure 5. Weekly Craving Measure During the Course of Treatment

eFigure 6. Survival Analysis to Discontinuation of Medication as Defined by the Subject Taking No Medication Past the Point of Survival

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