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 Author manuscript; available in PMC 2009 Sep 29.
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Am J Addict. 2009 Jul–Aug; 18(4): 301–308.
doi: 10.1080/10550490902927785PMCID: PMC2753886NIHMSID: NIHMS141953PMID: 19444734
Intermittent Marijuana Use Is Associated with Improved Retention in Naltrexone Treatment for Opiate-Dependence


Naltrexone is a theoretically promising alternative to agonist substitution treatment for opioid dependence, but its effectiveness has been severely limited by poor adherence. This study examined, in an independent sample, a previously observed association between moderate cannabis use and improved retention in naltrexone treatment. Opioid dependent patients (N = 63), admitted for inpatient detoxification and induction onto oral naltrexone, and randomized into a six-month trial of intensive behavioral therapy (Behavioral Naltrexone Therapy) versus a control behavioral therapy (Compliance Enhancement), were classified into three levels of cannabis use during treatment based on biweekly urine toxicology: abstinent (0% cannabis positive urine samples); intermittent use (1% to 79% cannabis positive samples); and consistent use (80% or greater cannabis positive samples). Intermittent cannabis users showed superior retention in naltrexone treatment (median days retained = 133; mean = 112.8, SE = 17.5), compared to abstinent (median = 35; mean = 47.3, SE = 9.2) or consistent users (median = 35; mean = 68.3, SE = 14.1) (log rank = 12.2, df = 2, p = .002). The effect remained significant in a Cox model after adjustment for baseline level of heroin use and during treatment level of cocaine use. Intermittent cannabis use was also associated with greater adherence to naltrexone pill-taking. Treatment interacted with cannabis use level, such that intensive behavioral therapy appeared to moderate the adverse prognosis in the consistent cannabis use group. The association between moderate cannabis use and improved retention on naltrexone treatment was replicated. Experimental studies are needed to directly test the hypothesis that cannabinoid agonists exert a beneficial pharmacological effect on naltrexone maintenance and to understand the mechanism.


Opioid dependence is a serious public health problem, with endemic opioid dependence having been joined over the past decade by a growing epidemic of prescription opioid dependence. Fortunately, effective treatments are available, but the majority of opioid dependent patients are not engaged in any treatment, while rates of dropout from treatment and relapse are high. Opioid substitution treatments, with methadone or buprenorphine, have consistent evidence of efficacy from multiple clinical trials, but even there rates of dropout and relapse are substantial. Dropout is usually associated with relapse. Treatment failure and ongoing opioid use have serious consequences, including morbidity and mortality from overdose and infectious diseases., Thus, factors that may improve retention deserve close scrutiny.Factors associated with better retention in methadone maintenance include demographic characteristics of patients, such as older age, being employed, being married, having effective social supports and good health., Importantly, features of methadone treatment programs are also associated with better outcome, including adequate methadone dosage, adequate counseling, presence of ancillary psychosocial services, emphasis on abstinence, and patient satisfaction.Naltrexone is a theoretically promising treatment for opioid dependence with a different mechanism of action, opioid antagonism, and potential advantages including lack of agonist effects or abuse potential. However, in practice the effectiveness of naltrexone has been severely limited by poor adherence. The ease with which naltrexone pills can be discontinued, the need for patients to be fully detoxified before starting naltrexone, and potential for precipitated withdrawal symptoms are likely contributing factors. Severity of opioid dependence and recent use of methadone have been associated with greater likelihood of dropout from naltrexone treatment. Coupling of naltrexone with enhanced behavioral interventions has been shown to improve retention, but dropout rates are still high.We previously reported a surprising finding that opioid dependent patients with intermittent cannabis use during naltrexone treatment showed better retention than patients with either heavy cannabis use, or no cannabis use, suggesting an inverted U-shaped function. This analysis was prompted by clinical observations that some opioid dependent patients on naltrexone reported benefit from cannabis use. However, this finding goes against conventional wisdom that other substance use during treatment would be associated with poor outcome, perhaps reflecting greater overall severity of addiction, or by functioning as a conditioned cue prompting return to opioid use. Other substance use is common among patients during treatment for opioid dependence,, but studies of its impact on treatment outcome have been mixed. Interestingly, a number of studies have found the impact of concurrent cannabis use on outcome of treatment for opioid dependence to be neutral. One study found concurrent cannabis use associated with poorer psychosocial functioning, but not with dropout among naltrexone treated opioid dependent patients. Another study found concurrent cannabis use associated with poorer outcome for alcohol and cocaine dependence, but not for opioid dependence.In this report, we sought to replicate the association between intermittent cannabis use and treatment retention in a different sample of opioid dependent patients undergoing naltrexone treatment, and to examine its impact on other outcomes. Since this was a randomized trial comparing intensive behavioral treatment (Behavioral Naltrexone Therapy, to a control treatment (Compliance Enhancement), we also examined whether the level of behavioral treatment influences the relationship between cannabis use and outcome. We also searched for demographic and clinical differences between patients that might confound an observed relationship between cannabis use and outcome.


Participants, Screening, and Procedure

The sample of patients presented in this report participated in a controlled trial of Behavioral Naltrexone Therapy (BNT) reported previously. One hundred and five treatment-seeking, opiate dependent, potential participants were evaluated, of which 80 were eligible and 69 completed inpatient detoxification and were randomized. Of these, 63 patients attended at least one outpatient visit and constitute the sample under study in this report. As part of the screening procedure, potential participants were evaluated with the Structured Clinical Interview for DSM-III-R Substance Abuse Comorbidity version (SCID-SAC), and by a psychiatric, medical and laboratory examination. Patients were eligible if they met DSM-IV criteria for current opiate dependence, were seeking treatment voluntarily, and had an abstinent significant other who could commit to participate in the treatment. Exclusion criteria included any unstable medical or psychiatric disorder that could make participation hazardous. After giving consent, patients were detoxified in hospital for up to 10 days, and then entered outpatient naltrexone maintenance lasting six months. Following the detoxification, patients were randomly assigned to one of two therapies: BNT or compliance enhancement (CE). All patients received oral naltrexone, titrated up to a dose of 50 mg a day, encapsulated with riboflavin to estimate compliance by urine fluorescence.

Psychosocial Therapy

Behavioral Naltrexone Therapy, described in detail elsewhere,, is a manual-guided intervention that combines evidence-based approaches, including Motivational Interviewing, Cognitive Behavioral Relapse Prevention,, Voucher Incentives, and Network Therapy with a significant other monitoring medication-taking, in an effort to optimize outcome of naltrexone treatment for opioid dependence. Its goals are to encourage continuous naltrexone adherence and abstinence from opiates. Individual treatment sessions occur three times per week for the first two weeks post-detoxification, and two times per week thereafter.Compliance Enhancement is also a manual-guided intervention intended to control for professional attention, and to simulate standard medical management. It consists of two appointments per week, one with a psychiatrist for counseling and another for clinical monitoring. The counseling consists of psychoeducation, emphasis on compliance with daily naltrexone intake, problem-solving, and 12-step principles.

Urine Collection and Analysis

During the six months of the BNT trial urine samples were collected under supervision at each twice-weekly visit. All collected urine samples were tested for illicit opiates, cocaine, benzodiazepines, and cannabis using Abbott//MDTX and scored as positive or negative using standard NIDA cutoffs, and viewed under ultraviolet light for riboflavin fluorescence, a marker of compliance with naltrexone treatment.

Data Analyses

Participants in the study were divided into three groups, based on how the proportion of cannabis positive urines collected during the trial was distributed. The abstinent cluster demonstrated no cannabis positive urines during their treatment (0% cannabis positive). For the intermittent use cluster between 1% and 79% of their urine samples were positive for cannabis. The consistent use cluster showed greater than 80% cannabis positive urines. Differences among the Cannabis Use groups on baseline demographics, baseline drug use, and continuous treatment outcomes were tested with chi-square or ANOVAs.Treatment retention was the primary outcome measure. Retention was defined as the numbers of days to dropout. Patients who relapsed (reverted back to opiate dependence) or did not attend the clinic at least once within a 14-day period were rated as treatment dropouts. The day on which the patient relapsed and was removed from the trial, or the 14th day of treatment absence was designated as the time of dropout. For those completing the trial, the 182nd day was the point of censor. The effect of cannabis use on time to drop out was tested using a Cox proportional hazard model. Variables were entered into the model in three blocks. Block 1 consisted of treatment group assignment, baseline heroin use (average bags per day), and cocaine use (proportion of cocaine-positive urines during the treatment). Cocaine use (based on urine toxicology data) during the treatment differed across the three cannabis use groups thus it was entered as a control variable. Benzodiazepine and alcohol use was rare during the trial and did not significantly differ across the three cannabis use groups. In Block 2 the main effects of cannabis use were tested by the simultaneous entry of two comparisons: abstinent vs. intermittent cannabis use, and abstinent vs. consistent cannabis use. In Block 3, the moderating effect of treatment group on the relationship between cannabis use and treatment retention was tested by entering two interaction terms: a treatment by intermittent cannabis use term and treatment by consistent cannabis use term, respectively. Changes in −2 Log Likelihood statistics tested the significance of each block entry. An alpha of 0.10 was used to test the entry of the treatment by cannabis use group interaction terms in block 3.Compliance with naltrexone treatment was calculated from the proportion of collected urine samples in the abstinent, intermittent, and consistent MJ groups that fluoresced for riboflavin under ultraviolet light. Means and standard deviations were compared by Chi-Square analysis.To evaluate if patients changed their cannabis use during the trial, we compared baseline self-reports of the proportion of days during which cannabis was used to the proportion of cannabis positive urine toxicology collected during the trial, trichotomized into abstinent, intermittent, and consistent cannabis use categories as described above.



Among the 63 opiate-dependent patients who attended at least one post-detoxification clinic appointment, 52 (83%) were men, 11 (17%) were women, and most were Caucasian (Caucasian 54%; African-American 16%; Hispanic 30%). The average age was 35.5 years (SD = 9.2) and 81% were not in a relationship during the treatment period. The average level of heroin use was 6.5 bags per day (SD = 3.6). The majority of patients reported intranasal use of heroin. Thirty-one were randomized to CE and 32 to BNT.No significant differences among the cannabis use groups were found concerning demographic variables, although there was a trend toward more Caucasians among the intermittent users. However, differences in baseline drug use were noted (Table 1). In the 30 days preceding entry in the trial, baseline number of heroin bags per day used increased as consumption of MJ increased across cannabis use groups. Consistent cannabis users reported a greatest proportion of cannabis use days (0.24), while intermittent users differed only slightly from abstinent users (0.06 vs. 0.01) in the proportion of cannabis use days.


Baseline demographic, drug use, treatment condition by cannabis use

Cannabis use
VariableAbstinent (n = 24)Intermittent (n = 18)Consistent (n = 21)Test statisticAge37.9 (9.23)35.9 (13.4)34.8 (9.4)F(2,60) = 1.0; p < .36Female (%)3 (12.5%)6 (33.3%)2 (9.5%)Relationship (%)7 (29.2%)1 (5.6%)4 (19.0%)X2(2)=3.7; p < .16Race African-American4 (16.7%)1 (5.6%)5 (23.8%) Hispanic7 (29.2%)4 (22.2%)8 (38.1%) White13 (54.2%)13 (72.2%)8 (38.1%)X2(2)=4.5; p < .10a Baseline Depression (HAM-D)15.0 (7.3)17.7 (6.8)15.3 (9.8)F(2,60) = 0.4; p < .65 % with anxiety or depressive disorder Dx54% (n = 13)44% (n = 8)43% (n = 9)X2(2)=0.68; p = .71 % with antisocial PD Dx88% (n = 21)94% (n = 17)86% (n = 18)X2(2)=0.82; p = .66Baseline Drug Use Bags per day (heroin)5.4 (3.3)6.0 (1.9)6.7 (4.7)F(2,60) = 3.7; p < .032 Proportion of days of cannabis use0.01 (0.03)0.06 (0.10)0.24 (0.33)F(2,51) = 17.2; p < .001 Proportion of days of opiate use1.00 (0.00)0.88 (0.28)0.97 (0.10)F(2,51) = 2.7; p < .08 Proportion of days of cocaine use0.02 (0.05)0.14 (0.280.06 (0.10)F(2,51) = 2.5; p < .10 % methadone use92% (n = 22)94% (n = 17)95% (n = 20)X2(2)=.27; p = .88Administration Route IN15(62.5%)9 (50.0%)15 (71.4%)X2(2)=1.1; p < .59a IV9 (37.5%)8 (44.4%)6 (28.6%) Smoke0 (0.0%)1 (5.6%)0 (0.0%)Tx Group BNT11(45.8%)8 (44.4%)13 (61.9%)X2(2)=1.6; p < .46 CE13(54.2%)10 (55.6%)8 (38.1%)
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Note: Administration route was tested as IV versus other routes; Racial differences as Caucasian versus other.

Changes in Pattern of Cannabis Use Before vs. After Treatment Entry

The pattern of cannabis use before treatment entry was classified into abstinent, intermittent, or consistent use based on self-reported use frequency at baseline and was compared to the during-treatment pattern based on urine toxicology. Sixty percent of abstinent cannabis users at baseline remained abstinent, 31% became intermittent users, and 9% became consistent users during the trial. Thirty three percent of intermittent users at baseline remained intermittent, 11% became abstinent, and 56% became consistent cannabis users. All consistent users at baseline remained so during the trial. These data are imprecise since serial urine toxicology data were not available pre-treatment, necessitating reliance on self-report to classify pre-treatment levels. Bearing that caveat in mind, the overall pattern was for patients to either remain at the same use level, or advance to a higher level of use.

Effect of Cannabis Use on Treatment Outcome 

Treatment outcome for the three cannabis use groups is summarized in Table 2, and the survival curves describing treatment retention across the groups are displayed in Figure 1. Intermittent cannabis users demonstrated longer treatment retention (median = 133 days) relative to those who were either abstinent (median = 35 days), or consistent (median = 35 days) users in either BNT or CE groups (log rank = 12.2, df = 2, p = .002). Cocaine use increased in proportion to the level of cannabis use, while the cannabis use groups did not differ on measures of opiate or benzodiazepine use during the treatment program. The Cox proportional hazards regression model, summarized in Table 3, yields a significant main effect of intermittent cannabis use on treatment retention, consistent with the descriptive data and the unadjusted log-rank test. Results modeling cannabis use (% THC positive urine toxicology) as a continuous variable yielded similar findings, supporting an inverted U shaped association between cannabis use and retention. There were no significant effects of baseline opioid use or during-treatment cocaine use. The model also yields a significant interaction of cannabis use level with randomized treatment condition. The interaction is driven by the heavy cannabis use group where treatment retention was better in the BNT treatment condition compared to the CE condition (see Figure 2), such that intensive behavioral therapy (BNT) appears to mitigate the adverse prognostic effect in the heavy cannabis use group, but not in the cannabis abstinent group. Compliance with naltrexone, assessed by the proportion of urine samples with riboflavin fluorescence differed by level of cannabis use (F(2,60) = 3.4; p < 0.03): intermittent users (mean = 0.86, SD = 0.22), abstinent users (mean = 0.56, SD = 0.41), consistent users (mean = 0.69, SD = 0.39).

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Treatment retention by marijuana use pattern (Abstinent (-▲-), Consistent Use (-●-), and Intermittent Use (-■-)).

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Treatment retention for consistent marijuana users by treatment condition (CE (-▲-), BNT (-■-).


Clinical outcome measures by cannabis use group

Cannabis use
VariableAbstinent (n = 24)Intermittent (n = 18)Consistent (n = 21)Test statisticProportion of cocaine positive urines.07 (.23).25 (.28).39 (.43)F(2,60) = 5.2; p < .009Proportion of benzodia-zepine positive urines.07 (.21).06 (.15).10 (.21)F(2,60) = 0.2; p < .85Proportion of treatment weeks opiates were used0.37 (0.39)0.25 (0.31)0.39 (0.42)F(2,60) = 0.8; p < .46Median Days in treatment3513335Diff log rank = 12.2, df = 2, p = .002
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Final Cox Regression Model testing the effect of marijuana use by treatment interaction on treatment retention

VariablesB (SE)Wald Chi-SquareSigHR (95% CI)Treatment−0.390 (.36)1.170.7610.68 (.33; 1.37)Baseline opioid use (Bags per day)0.045 (.05).830.301.05 (.95; 1.15)Cocaine Use during treatment0.030 (.50)0.000.951.03 (.39; 2.72)Intermittent cannabis use during-treatment−1.46 (.46) (.09; .57)Consistent cannabis use during treatment0.351 (.54)0.650.5161.42 (.49; 4.1)Treatment × Consistent Use−1.32 (.65)4.10.044–
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The present study replicates a previous surprising finding that intermittent cannabis use is associated with improved retention in naltrexone treatment among opioid dependent patients, while both abstinence from cannabis and regular cannabis use during naltrexone treatment are associated with high dropout. Inspection of the retention curves (Figure 1) shows that most of this effect occurs during the first 30 days after completion of inpatient detoxification and induction onto naltrexone, when dropout is steepest, and when patients may continue to experience protracted withdrawal that may be promoted by antagonist or inverse agonist effects of naltrexone. Intermittent cannabis use was also associated with improved adherence to naltrexone pill-taking. The data comparing cannabis use levels before versus after treatment entry suggest patients either stay at the same level, or advance to a higher level of cannabis use after starting naltrexone, consistent with a process of self-medication. These findings are of interest, because they suggest the hypothesis that moderate cannabis use may be exerting a beneficial pharmacological effect improving the tolerability of naltrexone in the early weeks after induction, and that cannabinoid agonists might have promise for improving the effectiveness of naltrexone treatment for opioid dependence.A beneficial effect of cannabinoid agonism early in the course of naltrexone treatment is biologically plausible. Rapid naltrexone induction during a 7 to 10 day hospitalization involves substantial withdrawal discomfort, which can be partially relieved by attenuating adrenergic activity with the alpha-2 autoreceptor agonist clonidine., During the early weeks after naltrexone induction, protracted withdrawal symptoms may persist, again likely driven in part by sympathetic nervous system activation., Data from a variety of preclinical models suggest that exogenous cannabinoids can attenuate sympathetic nervous activation, especially with intermittent rather than sustained administration. Thus, intermittent cannabis use might improve tolerability of naltrexone in the early weeks after induction by attenuating sympathetically driven withdrawal symptoms such as insomnia and agitation.Cannabis also stimulates appetite and has antiemetic, antispasmodic and analgesic effects that have been clinically useful during cancer chemotherapy and wasting syndromes., This might be useful in helping relieve the gastrointestinal distress and other physical discomfort associated with opioid withdrawal.Finally, cannabis might improve the tolerability of naltrex-one maintenance by furnishing an indirect dopaminergic agonist effect at the brain reward system, countering the lethargy and anhedonia that are typical of opioid withdrawal and that might be worsened or prolonged by antagonist or inverse agonist effects of naltrexone. Naltrexone has not generally been associated with anhedonia among normal controls or alcohol dependent patients., However, preclinical evidence suggests naltrexone functions as an inverse agonist in the setting of prior exposure to mu agonists, as in opioid dependence. Cannabinoid (CB1) and mu opiate receptors are both G protein coupled receptors with overlapping neuroanatomical localization, and both CB1 and mu agonists stimulate dopamine release from the meso-limbic dopamine neurons and function as positive reinforcers. Thus, cannabis might compensate for a deficit in dopaminergic tone related to naltrexone.The hypothesis of a beneficial pharmacological effect of cannabis for naltrexone maintenance would need to account for the inverted U-shaped function, namely that heavier cannabis use was associated with worse treatment retention than intermittent use. It may be that heavy cannabis use identifies a subgroup with greater overall addiction severity and worse prognosis that overwhelms any beneficial pharmacological effect of cannabis. This would be consistent with the significant association between cannabis use level and baseline level of opioid use (bags per day) (see Table 1), which has been shown to be a predictor of poor outcome for naltrexone maintenance. In prior analyses, the intensive behavioral therapy (BNT) was shown to have its greatest beneficial effect among patients with the higher levels of opioid dependence (more bags per day) at baseline., Similarly here, the interaction of treatment assignment with level of cannabis use suggests that BNT partially counteracts the adverse prognosis in the heavy cannabis use group (Table 3, and Figure 2).It is possible that regular or heavy cannabis use induces tolerance, perhaps through down regulation of CB1 receptors, diminishing any beneficial effects. The inverted U pattern might also reflect individual differences in sensitivity to the putative beneficial effect of cannabis. Since patients would be self-medicating, in effect adjusting their own dosages, those who are most responsive to the beneficial effects might select a modest dosage level sufficient to provide substantial relief, whereas those who are less responsive may advance to more regular or heavy use without sufficient response to impact retention.The present findings are observational, and it is also possible that the association between intermittent cannabis use and improved retention on naltrexone is accounted for by unmeasured confounds or other mechanisms, rather than a causal pharmacological effect. Baseline level of heroin use (bags per day), the most consistent predictor of naltrexone treatment in our hands,,, was controlled for in the Cox model, suggesting severity of opioid dependence at baseline is not a confound. Another approach is to consider why patients without any concurrent cannabis use would have poor outcome. For example, it has been theorized that complete abstinence early in treatment may be stressful for patients who have long relied on substance use as a coping mechanism. It is also possible that the cannabis abstinent group differs in their response to cannabis, experiencing it as either not reinforcing or aversive, based on constitutional or neurobiological factors that also might be associated with poor response to naltrexone.Experimental studies are needed to determine whether cannabinoid agonists may exert a beneficial effect on opioid withdrawal or naltrexone maintenance. Haney and colleagues examined the impact of naltrexone (versus placebo) on cannabis effects, finding that naltrexone at 50 mg, but not 12 mg, increased the intoxicating effects of cannabis in established smokers, while in participants without a history of cannabis use, 12 mg of naltrexone enhanced the effect of cannabis. Such a mechanism might explain the inverted-U pattern if naltrexone caused excessive and aversive cannabis effects among the heavy users. In any case, it suggests there may be meaningful pharmacological interactions between cannabinoid and opioid systems, and that these may be conditioned by the prior history of use.Experimental, placebo-controlled studies are needed to directly examine whether cannabinoid agonists are effective as adjuncts to opioid detoxification or naltrexone maintenance treatment and to delineate the mechanism. Oral THC (Dronabinol) is FDA approved to counteract appetite suppression and wasting syndromes and would be available in the U.S. for study. Sativex, which includes both THC and cannabidiol, is available in Canada. Other cannabinoid agonists or partial agonists might be considered as they become available for study in the future. Small, within-subjects crossover studies in the human laboratory could examine effects of cannabinoid agonists on acute opioid withdrawal, or naloxone precipitated withdrawal. Larger placebo-controlled clinical trials should examine cannabinoid effects as adjuncts to opioid detoxification or naltrexone maintenance treatment. Success in these efforts could advance the field by improving the viability of naltrexone in the treatment armamentarium for opioid dependence. Issues regarding exposing patients to a medication with its own addictive potential would also need to be carefully addressed.


This work was partially supported by grants RO1 KO2 DA00288 (Dr. Nunes), P50-DA009236 (Dr. Herbert Kleber), and K24 DA 022412 (Dr Nunes) from the National Institute on Drug Abuse, Bethesda, Md.The authors thank Dr. Mary Bonjiovi and her clinical staff for clinical support throughout this study. Gratitude is expressed to Lisa Sanfilippo for editorial assistance.


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1. Blanco C, Alderson D, Ogburn E, et al. Changes in the prevalence of non-medical prescription drug use and drug use disorders in the United States: 1991–1992 and 2001–2002. Drug Alcohol Depend. 2007;90:252–260. [PubMed] []2. Mattick RP, Kimber J, Breen C, Davoli M. Buprenorphine maintenance versus placebo or methadone maintenance for opioid maintenance. Cochrane Database Syst Rev. 2008;16:CD002207. [PubMed] []3. Johansson BA, Berglund M, Lindgren A. Efficacy of maintenance treatment with naltrexone for opioid dependence: a meta-analytical review. Addiction. 2006;101:491–503. [PubMed] []4. Davoli M, Perucci CA, Forastiere F, Doyle P, Rapiti E, Zaccarelli M. Risk factors for overdose mortality: a case-controlled study within a cohort of intravenous drug users. Int J Epidemiol. 1993;22:273–277. [PubMed] []5. Zaric GS, Barnett PG, Brandeau ML. HIV transmission and the cost-effectiveness of methadone maintenance. Am J Public Health. 2000;90:1100–1111. [PMC free article] [PubMed] []6. Mertens JR, Weisner CM. Predictors of substance abuse treatment retention among women and men in an HMO. Alcohol Clin Exp Res. 2000;24:1525–1533. [PubMed] []7. Saxon AJ, Wells EA, Fleming C, Jackson TR, Calsyn DA. Pre-treatment characteristics, program philosophy, and level of ancillary services as predictors of methadone maintenance treatment outcome. Addiction. 1996;91:1197–1209. [PubMed] []8. Stark MJ. Dropping out of substance abuse treatment: a clinically oriented review. Clin Psychol Rev. 1992;12:93–116. []9. Caplehorn JRM, Bell J. Methadone dosage and retention of patients in maintenance treatment. Med J Aust. 1991;154:195–199. [PubMed] []10. McLellan AT, Arndt IO, Metzger DS, Woody GE, O’Brien CP. The effects of psychosocial services in substance abuse treatment. JAMA. 1993;269:1953–1959. [PubMed] []11. Torrens M, Castillo C, Perez-Sola V. Retention in a low-threshold methadone maintenance program. Drug Alcohol Depend. 1996;41:55–59. [PubMed] []12. Del Rio M, Mino A, Perneger TV. Predictors of patient retention in a newly established methadone maintenance treatment program. Addiction. 1997;92:1353–1360. [PubMed] []13. Rhoades HM, Creson D, Elk R, Schmitz J, Grabowski J. Retention, HIV risk, and illicit drug use during treatment: methadone dose and visit frequency. Am J Public Health. 1998;88:34–39. [PMC free article] [PubMed] []14. Caplehorn JRM, Lumley TS, Irwig L. Staff attitudes and retention of patients in methadone maintenance programs. Drug Alcohol Depend. 1998;52:57–61. [PubMed] []15. Preston KL, Umbricht A, Epstein DH. Methadone dose increase and abstinence reinforcement for treatment of continued heroin use during methadone maintenance. Arch Gen Psychiatry. 2000;57:395–404. [PubMed] []16. Sullivan MA, Rothenberg JL, Vosburg SK, et al. Predictors of retention in naltrexone maintenance for opioid dependence: analysis of a stage 1 trial. Am J Addict. 2006;15:150–159. [PubMed] []17. Amato L, Minozzi S, Davoli M, Vecchi S, Ferri M, Mayet S. Psychosocial combined with agonist maintenance treatments versus agonist maintenance treatment alone for treatment of opioid dependence (review) The Cochrane Library. 2006;3:1–30. [PubMed] []18. Villafranca SW, McKellar JD, Trafton JA, Humphreys K. Predictors of retention in methadone programs: a signal detection analysis. Drug Alcohol Depend. 2006;83:218–224. [PubMed] []19. Preston KL, Silverman K, Umbricht A, DeJesus A, Montoya ID, Schuster CR. Improvement in naltrexone treatment compliance with contingency management. Drug Alcohol Depend. 1999;54:127–135. [PubMed] []20. Carroll KM, Ball SA, Nich C, et al. Targeting behavioral therapies to enhance naltrexone treatment of opioid dependence: efficacy of contingency management and significant other involvement. Arch Gen Psychiatry. 2001;58:755–761. [PMC free article] [PubMed] []21. Carroll KM, Sinha R, Nich C, Babuscio T, Rounsaville BJ. Contingency management to enhance naltrexone treatment of opioid dependence: a randomized clinical trial of reinforcement magnitude. Exp Clin Psychopharmacol. 2002;10:54–63. [PubMed] []22. Fals-Steward W, O’Farrell TJ. Behavioral family counseling and nal-trexone for male opioid dependent patients. J Consult Clin Psychol. 2003;71:432–442. [PubMed] []23. Church SH, Rothenberg JL, Sullivan MA, Bornstein G, Nunes EV. Concurrent substance use and outcome in combined behavioral and naltrexone therapy for opiate dependence. Am J Drug Alcohol Abuse. 2001;27:441–452. [PubMed] []24. Nunes EV, Rothenberg JL, Sullivan MA, Carpenter KM, Kleber HD. Behavioral Therapy to Augment Oral Naltrexone for Opioid Dependence: A Ceiling on Effectiveness? Am J Drug Alcohol Depend. 2006;32:503–517. [PubMed] []25. Nirenberg TD, Celluci T, Liepman MR, Swift R, Sirota D. Cannabis versus other illicit drug use among methadone maintenance patients. Psychol Addict Behav. 1996;10:222–227. []26. DeMaria PA, Sterling R, Weinstein SP. The effect of stimulant and sedative use on treatment outcome of patients admitted to methadone maintenance treatment. Am J Addict. 2000;9:145–153. [PubMed] []27. Ellner M. Marijuana use by heroin abusers as a factor in program retention. J Consult Clin Psychol. 1977;45:709–710. [PubMed] []28. Budney AJ, Bickel WK, Amass L. Marijuana Use and treatment outcome among opioid-dependent patients. Addiction. 1998;93:493–503. [PubMed] []29. Weizman T, Gelkopf M, Melamed Y, Adelson M, Bleich A. Cannabis abuse is not a risk factor for treatment outcome in methadone maintenance treatment: a 1-year prospective study in an Israeli clinic. Aust NZ J Psychiatry. 2004;38:42–46. [PubMed] []30. Epstein DH, Preston KL. Does cannabis use predict poor outcome for heroin-dependent patients on maintenance treatment? Past findings and more evidence against. Addiction. 2003;98:269–279. [PMC free article] [PubMed] []31. Rothenberg J, Sullivan MA, Church SH, et al. Behavioral naltrexone therapy: an integrated treatment for opiate dependence. J Subst Ab Res. 2002;23:351–360. [PubMed] []32. Carroll KM, Nuro KR, O’Malley SS. Yale University School of Medicine. New Haven, CT: Psychotherapy Development Center, Department of Psychiatry; 1999. Compliance enhancement: a manual for the clinical management of drug-dependent patients. []33. Nunes EV, Goehl L, Seracini A, et al. Evaluation of depression and panic disorder in methadone patients using a modification of the structured clinical interview for DSM-III-R: test-retest reliability. Am J Addict. 1996;5:241–248. []34. Miller WR, Rollnick S. Motivational Interviewing. London, England: Guilford Press; 2002. []35. Carroll KM, Rounsaville BJ, Nich C, Gordon LT, Wirtz PW, Gawin F. One-year follow-up of psychotherapy and pharmacotherapy for cocaine dependence. Delayed emergence of psychotherapy effects. Arch Gen Psychiatry. 1994;51:989–997. [PubMed] []36. Marlot GA, Gordon JR. Relapse prevention and maintenance strategies in the treatment of addictive behaviors. New York, NY: Guilford Press; 1985. []37. Silverman K, Wong CJ, Umbricht-Schneider A, Montoya ID, Schuster CR, Preston KL. Broad beneficial effects of cocaine abstinence reinforcement among methadone patients. J Consult Clin Psychol. 1998;66:811–824. [PubMed] []38. Silverman K, Chutuape MA, Bigelow GE, Stitzer ML. Voucher-based reinforcement of cocaine abstinence in treatment-resistant methadone patients: effects of reinforcement magnitude. Psychopharm (Berlin) 1999;146:128–138. [PubMed] []39. Stitzer ML, Iguchi MY, Felch LJ. Contingent take-home incentive: effect on drug use of methadone maintenance patients. J Consult Clin Psychol. 1992;60:927–934. [PubMed] []40. Higgins ST, Delaney DD, Budney AJ, et al. A behavioral approach to achieving initial cocaine abstinence. Am J Psychiatry. 1991;148:1218–1224. [PubMed] []41. Higgins ST, Budney AJ, Bickel WK, Hughes JR, Foerg F, Badger G. Achieving cocaine abstinence with a behavioral approach. Am J Psychiatry. 1993;150:763–769. [PubMed] []42. Higgins ST, Budney AJ, Bickel WK, Foerg FE, Donham R, Badger GJ. Incentives improve outcome in outpatient behavioral treatment of cocaine dependence. Arch Gen Psychiatry. 1994;51:568–576. [PubMed] []43. Galanter M. Network therapy for addiction: a model for office practice. Am J Psychiatry. 1993;150:28–36. [PubMed] []44. Wang D, Raehal KM, Bilsky EJ, Sadee W. Inverse agonists and neutral antagonists at mu opioid receptors (MOR): possible role of basal receptor signaling in narcotic dependence. J Neurochem. 2001;77:1590–1600. [PubMed] []45. Raehal KM, Lowery JJ, Bhamidipati CM, et al. In vivo characterization of 6beta-naltrexol, an opioid ligand with less inverse agonist activity compared with naltrexone and naloxone in opioid-dependent mice. J Pharmacol Exp Ther. 2005;313:1150–1162. [PubMed] []46. Divin MF, Holden Ko MC, Traynor JR. Comparison of opioid receptor antagonist properties of naltrexone and 6beta-naltrexol in morphine-naïve and morphine-dependent mice. Eur J Pharmacol. 2008;583:48–55. [PMC free article] [PubMed] []47. Kleber HD, Topazian M, Gaspari J, Riordan CE, Kosten T. Clonidine and Naltrexone in the outpatient treatment of heroin withdrawal. Am J Drug Alcohol Abuse. 1987;13:1–17. [PubMed] []48. Gowing L, Farrell M, Ali R, White J. Alpha2 adrenergic agonists for the management of opioid withdrawal. Cochrane Database Syst Rev. 2004 Oct 18;(4):CD002024. [PubMed] []49. Muntoni AL, Pillolla G, Melis M, Perra S, Gessa GL, Pistis M. Cannabinoids modulate spontaneous neuronal activity and evoked inhibition of locus coeruleus noradrenergic neurons. Eur J Neuroscience. 2006;23:2385–2394. [PubMed] []50. Poddar MK, Dewey WL. Effects of cannabinoids on catcholamine uptake and release in hypothalamic and striatal synaptosomes. J Pharmacol Exp Ther. 1980;214:63–67. [PubMed] []51. Jentsch DJ, Andrusiak BS, Tran A, Bowers MB, Roth RH. Delta-9-tetrahydrocannabinol increases prefrontal cortical catecholaminergic utilization and impairs spatial working memory in the rat: blockade of dopaminergic effects with HA966. Neuropsychopahrmacology. 1997;16:426–432. [PubMed] []52. Schlicker E, Timm J, Zentner J, Gothert M. Cannabinoid CB1 receptor-mediated inhibition of noradrenaline release in the human and guinea-pig hippocampus. Naunyn Schmiederbergs Arch Pharmacol. 1997;356:583–589. [PubMed] []53. Kathmann M, Bauer U, Schlicker E, Golthert M. Cannabinoid CB1 receptor-mediated inhibition of NMDA- and kainite stimulated noradrenaline and dopamine release in the brain. Naunyn Schmiederbergs Arch Pharmacol. 1999;359:466–470. [PubMed] []54. Trendelenburg AU, Cox SL, Schelb V, Klebroff W, Khairallah L, Starke K. Modulation of (3)H-noradrenaline release by presynaptic opioid, cannabinoid and bradykinin receptors and beta-adrenoreceptors in mouse tissues. Br J Pharmacol. 2000;130:321–330. [PMC free article] [PubMed] []55. Schlicker E, Kathmann M. Modulation of transmitter release via presynaptic cannabinoid receptors. Trends Pharmacol Sci. 2001;22:565–572. [PubMed] []56. Tzavara ET, Perry KW, Rodriguez DE, Bymaster FP, Nomikos GG. The cannabinoid CB(1) receptor antagonist SR141716A increases norepinephrine outflow in the rat anterior hypothalamus. Eur J Pharmacol. 2001;426:R3–R4. [PubMed] []57. Tzavara ET, Davis RJ, Perry KW, et al. The CB1 receptor antagonist SR141716A selectively increases monoaminergic neurotransmission in the medial prefrontal cortex: implications for therapeutic actions. Br J Pharmacol. 2003;138:544–553. [PMC free article] [PubMed] []58. Moranta D, Esteban S, Garcia-Sevilla JA. Differential effects of acute cannabinoid drug treatment, mediated by CB1 receptors, on the in vivo activity of tyrosine and tryptophan hydroxylase in the rat brain. Naunyn Schmiederbergs Arch Pharmacol. 2004;369:516–524. [PubMed] []59. Oropeza VC, Page ME, Van Bockstaele EJ. Systemic administration of WIN55,212–2 increases norepinephrine release in the rat frontal cortex. Brain Res. 2005;1046:45–54. [PubMed] []60. Niederhoffer N, Szabo B. Effect of the cannabinoid receptor agonist WIN55212-2 on sympathetic cardiovascular regulation. Br J Pharmacol. 1999;126:457–466. [PMC free article] [PubMed] []61. Vizi ES, Katona I, Freund TF. Evidence for presynaptic cannabinoid CB(1) receptor-mediated inhibition of noradrenaline release in the guinea pig lung. Eur J Pharmacol. 2001;431:237–244. [PubMed] []62. Pfizer T, Niederhoffer N, Szabo B. Search for an endogenous cannabinoid-mediated effect in the sympathetic nervous system. Naunyn Schmiedeberg Arch Pharmacol. 2005;371:9–17. [PubMed] []63. Ponto LL, O’Leary DS, Koeppel J, et al. Effects of acute marijuana on cardiovascular function and central nervous system pharmacokinetics of [(15)O]water: effects in occasional and chronic users. J Clin Pharmacol. 2004;44:751–766. [PubMed] []64. Aviello G, Romano B, Izzo AA. Cannabinoid and gastrointestinal motility: animal and human studies. Eur Rev Med Pharmacol Sci. 2008;(Suppl 1):81–93. [PubMed] []65. Machado Rocha FC, Stefano SC, De Cassia Haiek R, Rosa Oliviera LM, Da Silviera DX. Therapeutic use of cannabis sativa on chemotherapy-induced nausea and vomiting among cancer patients: systematic review and meta-analysis. Eur J Cancer Care (Engl) 2008;17:431–443. [PubMed] []66. Anton RF, O’Malley SS, Ciraulo DA, et al. Combined pharma-cotherapy and behavioral interventions for alcohol dependence. JAMA. 2006;295:2003–2017. [PubMed] []67. Kranzler HR, Wesson DR, Billot L Drug Abuse Sciences Naltrexone Depot Study Group. Naltrexone depot for treatment of alcohol dependence: a multicenter, randomized, placebo-controlled clinical trial. Alcohol Clin Exp Res. 2004;28:1051–1059. [PubMed] []68. Vasquez C, Lewis DK. The CB1 cannabinoid receptor can sequester G-proteins making them unavailable to couple to other receptors. J Neurosci. 1999;19:9271–9280. [PMC free article] [PubMed] []69. Sullivan MA, Rothenberg JL, Vosburg SK, et al. Predictors of retention in naltrexone maintenance for opioid dependence: analysis of a stage 1 trial. Am J Addict. 2006;15:150–159. [PubMed] []70. Carpenter KM, Jiang H, Sullivan MA, et al. Betting on change: modeling transitional probabilities to guide therapy development for opioid dependence. Psychol Addict Behav. 2009;23:47–55. [PMC free article] [PubMed] []71. Mason DJ, Lowe J, Welch SP. A diminution of delta-9-tetrahydrocannabinol modulation of dynorphin A-(1–17) in conjunction with tolerance development. Eur J Pharmacology. 1999;381:105–111. [PubMed] []72. Shedler J, Block J. Adolescent drug use and psychological health. Am Psychol. 1990;45:612–630. [PubMed] []73. Haney M, Bisaga A, Foltin RW. Interaction between naltrexone and oral THC in heavy marijuana smokers. Psychopharmacology (Berlin) 2003;166:77–85. [PubMed] []74. Haney M. Opioid antagonism of cannabinoid effects: differences between marijuana smokers and nonmarijuana smokers. Neuropsychopharmacology. 2007;32:1391–1403. [PubMed] []