An early report concluded that cannabis use in methadone-maintained patients “can interfere with treatment goals” (DuPont & Saylor, 1989). The authors tested more than 300 urine specimens (from an unstated number of patients) from two clinics, at which the respective rates of cannabinoid-positive urine specimens were 27% and 51%. The authors stated that all but one of the cannabinoid-positive specimens was also positive for another drug. However, their own data appear to contradict this, since at least 75% of the cannabinoid-positive specimens seem unaccounted for in the breakdown of other-drug positives (11% of the cannabinoid-positive specimens were positive for cocaine, 9.2% for opiates, 3% for benzodiazepines, and 1.8% for barbiturates). In addition, no base rates were given for other-drug positives in cannabinoid-negative urines (except benzodiazepines, for which the base rates—4% and 7% at the respective clinics—were slightly higher than the rate in cannabinoid-positive urines). Thus, despite the authors’ conclusion, it is not clear that cannabis use was associated with increased likelihood of other drug use.

Four subsequent reports have shown no association between cannabis use and other drug use among heroin-dependent patients in treatment.

Saxon et al. (1993) reported data from all male patients who had been in treatment for at least six months in 1989–1990 at a Seattle methadone clinic. Of the 98 men in the sample, 54 had tested positive for cannabinoids at least once in weekly urinalyses. They did not differ from the other 44 in their rates of other-drug positives. The cannabinoid-positive patients were then subdivided into consistent cannabis users (all tests positive, n=22) and intermittent cannabis users (not all tests positive, n=32). Other-drug positives were actually less frequent in the consistent cannabis users than in the intermittent cannabis users. In a superset (N=117) of the same patient sample, with no minimum treatment duration, results were essentially the same, and there was no association between cannabis use and treatment retention (Saxon et al., 1991).

Nirenberg et al. (1996) reported data from 70 patients (69 male) in an urban methadone-maintenance program; urine was tested weekly for 14 to 45 weeks. The sample was divided into cannabis abstainers (n=15), intermittent users (up to 33.3% positive; n=25); moderate users (33.3–66.6% positive; n=16); and consistent users (66.6–100% positive; n=14). Groups did not differ in their rates of other-drug positives (whereas patients positive for either cocaine or benzodiazepines did show higher rates of opiate positives).

Budney et al. (1998) examined 107 patients (68 male) maintained on buprenorphine in a treatment-research clinic in Vermont; urine was tested thrice weekly for up to 32 weeks. Seventy-one patients tested positive for cannabinoids at least once (or reported use in the 30 days before enrollment). To test associations with treatment outcome, the authors examined a subset of patients (n=79) who had received buprenorphine plus behavior therapy; 51 tested positive for cannabinoids at least once, but this was not associated with differences on any measure of treatment outcome (retention; opiate, cocaine, or benzodiazepine use; or changes in ASI scores from intake to 12 months later). Percentage of cannabinoid-positive urines did not correlate with weeks of heroin abstinence or with percentage of treatment weeks completed.

Church et al. (2001) examined 47 patients (36 male) maintained on methadone and naltrexone in a treatment-research clinic in New York City; urine was tested twice weekly for 6 months. 28 patients tested positive for cannabinoids at least once. Patients were trichotomized as cannabis-abstinent (n=13), intermittent users (n=18), and heavy users (n=10). The intermittent users actually had fewer opiate-positive urines and better naltrexone compliance than the cannabis-abstinent patients; the heavy users showed no differences from the abstinent patients. The meaningfulness of the trichotomy is questionable, since any patient with fewer than 100% of urines positive for cannabinoids was classified as an intermittent user. (The classification was based on an exaggeration of cannabinoids’ detection time in urine, which, at the standard cutoff of 50 ng/mL, should be only 2–3 days after one use [Huestis, Mitchell & Cone, 1995], and roughly 5 days in weekly users and 16–17 days in daily users [Smith-Kielland, Skuterud & Mørland, 1999; inferred from graphs of time-course data].) But across the whole sample, the percentage of cannabinoid-positive urines did not correlate with treatment retention, naltrexone compliance, or the percentage of opiate-, cocaine-, or benzodiazepine-positive urines.

Even before the publication of most of these negative findings, one group concluded that testing for cannabinoids in methadone clinics is not necessary or justified (Saxon et al., 1991, 1993), a conclusion that appears to have influenced practice at some clinics (Budney, personal communication, 2000).

Wasserman et al. (1998) took a different approach, and obtained more discouraging results. Their sample was drawn from four methadone-maintenance programs in the San Francisco area in 1992–1995; analyses were restricted to 74 patients (out of 528) who had stopped using heroin for at least three weeks (two weeks by self-report, then a baseline week of twice-weekly urinalyses). Thirty-five patients tested positive for cannabinoids at least once during the study. The goal of the analysis was to find predictors of subsequent lapses to heroin use (as indicated by at least one heroin-positive urine) during seven further weeks of twice-weekly urinalyses. Lapses occurred in 30 patients (and were followed by recurrent opiate positives in 21 of those patients). Lapses were significantly predicted by only two variables out of 20: not having a goal of absolute heroin abstinence, and testing positive for cannabinoids. Cannabinoid positives were predictive in either of two analyses—one in which cannabinoid positives during the baseline week were treated as a baseline predictor, and one in which cannabinoid positives throughout the study were treated as a time-dependent predictor. No contingency table, effect size, or hazard ratio was given, but using the χ² value (7.62 for the second analysis) and the marginals, we estimated a relative risk of (21/35)/(9/39) = 2.6. The findings of Wasserman et al. (1998) suggest that for patients who have stopped using heroin, cannabinoid-positive urine is a robust predictor of resumption of heroin use.

Two more questions have received relatively little attention. First, is cannabis use among methadone patients problematic in its own right? That is, even if it does not predict increased use of other drugs, does it predict poorer outcomes in general psychosocial functioning at posttreatment follow-up? This was tested in only one of the studies cited above (Budney et al., 1998), and the answer appeared to be no. Second, should the main object of concern be cannabis abuse/dependence rather than use? That is, will differences in treatment outcome be greater if patients are categorized by whether they meet criteria for a cannabis-use disorder? This approach was used in a report on cocaine-dependent patients (Budney, Higgins & Wong, 1996), but to our knowledge, has not yet been used in any reports on methadone-maintained patients.

We set out first to determine whether the patterns of findings in previous studies would be replicated in our larger sample. (For the previous studies, the mean sample size was 79 [range 47–107], and the mean number of cannabinoid-positive patients was 49 [range 28–71].) We pooled data from three of our completed clinical trials, with sample sizes of 120, 95, and 193, in which the respective numbers of cannabinoid-positive patients were 55, 71, and 94.) We then examined data from follow-up evaluations conducted 3, 6, and 12 months posttreatment, to determine whether cannabis use during treatment predicts subsequent unemployment, percent of income spent on drugs, days of illegal activity, days of imprisonment, and interpersonal conflict. Finally, we tested whether the outcomes of interest, during and after treatment, were more closely associated with cannabis abuse/dependence than with cannabis use.

The statistical power of our analyses also indicates that if cannabis use predicts lapse to heroin use among patients who have become heroin-abstinent, the hazard ratio is unlikely to be greater than 2.22. A hazard ratio of that magnitude may be clinically significant, but the actual hazard ratio may be considerably lower; in our sample it was 1.54 at most and not statistically significant. This finding contradicts that of Wasserman et al. (1998). Interpretation of the discrepancy is complicated by a difference in the overall rate of lapse (more than 80% in our patients versus 41% in Wasserman et al.’s patients), which might have obscured any influence of cannabis use in our sample. The difference in overall rate of lapse may have been due to other sample differences (Wasserman et al.’s patients were given a wider, presumably more individualized range of methadone doses, and had generally been at their maintenance dose longer than our patients), and those differences themselves may have moderated any effect of cannabis use. It is also worth noting that our sample, though comparable to that of Wasserman et al. in terms of sex, age, education, and income, had a greater proportion of African-Americans, a slightly lower rate of unemployment, and, moreover, a far lower lifetime rate of psychiatric disorders (43% vs. 1% for Major Depressive Disorder, 49% vs. 6% for PTSD, and 43% vs. 13% for Antisocial Personality Disorder). Psychiatric diagnoses did not predict lapse in Wasserman et al.’s patients, but they did not test for an interaction of cannabis use with psychiatric diagnoses. Thus, it is possible that cannabis use differentially predicts lapse to heroin use in patients with psychiatric comorbidity. Finally, it is possible that the finding of Wasserman et al. (1998) was due to chance; cannabis use was one of 20 predictors tested in that study, and with a Bonferroni correction, its p value increases from .004 to .08.

Our finding that cannabis use was not associated with treatment retention is consistent with others’ findings (Saxon et al., 1991; Budney et al., 1998; Church et al., 2001). In fact, one report on 120 patients in a drug-free treatment program for heroin addiction suggested that marijuana use was a favorable prognostic factor for treatment retention (Ellner, 1977).

Our findings could be taken to suggest that if cannabis use in methadone patients is to be discouraged, it should be for its own sake, not for the sake of a presumed causal relationship with treatment dropout or heroin or cocaine use. But even this interpretation may be too broad, because, in our posttreatment follow-ups, cannabis use during treatment failed to predict any of the psychosocial problems assessed by the ASI. Two of the psychosocial problems (number of recent days in jail and number of recent days of family conflict) were predicted, albeit weakly, by lifetime history of Cannabis Abuse or Dependence. Thus, the negative prognostic signs of interest may be symptoms of Cannabis Abuse or Dependence.

Counterintuitively, Cannabis Abuse or Dependence predicted less use of heroin and cocaine during treatment itself. This seems to replicate a prior finding among cocaine-dependent patients: durations of abstinence from cocaine were significantly longer in patients with comorbid Cannabis Dependence (Budney et al., 1996). It is unlikely that this could be explained by patients’ substituting cannabis for heroin or cocaine; if substitution were occurring, one would expect to see an association with frequency of cannabis use, not with symptoms of Cannabis Abuse or Dependence. (In any case, behavioral-economic work has shown that cannabis is at best a weak substitute for heroin; Petry & Bickel, 1998.) Since criteria were met through self-report via a structured interview, meeting criteria might be a marker of greater insight into drug-associated problems. This is consistent with our own recent finding that cocaine use during treatment was lower in methadone patients who had met criteria for Cocaine Dependence at intake (Epstein et al., in press).

However, even if meeting DSM criteria for Cannabis Abuse or Dependence were a marker of greater insight, we found that patients who met criteria were continuing to use more cannabis than those who did not. This combination of findings—self-reported adverse consequences of cannabis use, plus continued use—is reason enough for cannabis use to be a focus of clinical attention within this subgroup of patients. In our sample, patients reported symptoms such as using more cannabis than intended and being high on cannabis when expected to perform role obligations or when hazardous. These self-reported symptoms seem to provide a good basis for encouraging the patient to reduce or discontinue cannabis use.

This finding is complicated by the fact that, in the 11 patients for whom recency data were available, eight reported that no symptoms had occurred within the past year. There is insufficient evidence to say what level of concern should be generated by continued cannabis use in a patient who endorses a past history of Cannabis Abuse or Dependence. Studies of the natural history of these disorders (Rosenberg & Anthony, 2001; von Sydow et al., 2001) have not addressed the issue, and have not been done in methadone-maintained heroin addicts. In clinical practice, changes in the number or severity of DSM-IV symptoms of Cannabis Abuse or Dependence can be assessed through a semistructured interview (although reliability is not as good as for other diagnostic categories) (Miele et al., 2000). Formal or informal use of such an instrument might serve as a barometer for reemergence of past symptoms.

The present study has limitations that should be considered. The most important is that, except when the DIS was given at study intake, we did not directly ask participants about the consequences of their cannabis use. We also limited the sensitivity of our analyses by categorizing cannabis use rather than treating it as a continuous variable. (However, it is our impression that most methadone-clinic staff and administrators view cannabis use as a behavior categorically distinct from abstinence. By categorizing levels of use, we struck a balance between having more sensitive analyses and having results expressible in terms that would be meaningful to most clinicians. Moreover, when we repeated some of our analyses after coding cannabis use as a continuous predictor, the results did not change.) After the first five weeks of treatment, all of our participants either underwent contingency management or a control condition (with vouchers given noncontingently); we do not have data from patients in more conventional long-term methadone maintenance. (This limitation carries one analytic advantage: our patients were not discharged for using heroin or cocaine, so rates of use were not artificially low.) Although we tried to enroll participants representative of the urban area our clinic serves, we excluded study applicants with symptoms of psychosis, mania, or active suicidal ideation, or with physical dependence on alcohol or sedatives; thus, our findings may not generalize to patients with such comorbidities. Due to the time-limited nature of our studies, no patient was enrolled in our clinic for more than 39 weeks, and our posttreatment follow-up for each patient was limited to three appointments in 12 months; therefore, we may have failed to detect long-term adverse outcomes. Our diagnoses of substance-use disorders were not based on the most recent edition of the DSM, and due to the archival nature of the data, we had only diagnostic summaries for most participants.

Another possible limitation is that our cannabinoid-positive participants did not test positive as frequently, on average, as those in other studies. Overall, 54% tested positive at least once. (For comparison, the corresponding figures from prior studies are 47% [Wasserman et al., 1998], 55% [Saxon et al., 1993], 65% [Budney, Bickel & Amass, 1998] and 79 % [Nirenberg et al., 1996].) However, among the subgroup who tested positive, only 11 (5%) of them tested positive every time. For comparison, the corresponding figure from another study is 41% (Saxon et al., 1993). Similarly, if we use the classification chosen by Nirenberg et al. (1996), the percentages of intermittent, moderate, and consistent users (up to 1/3 positive, 1/3 to 2/3 positive, and 2/3 to all positive) among our users were 68%, 17%, and 15%; among the users described in Nirenberg et al. (1996), the percentages were 45%, 29%, and 25%. The percentage of our users who met DSM criteria for a cannabis-use disorder (15%) was similar to the 17% reported by Budney, Bickel & Amass (1998).

It might be argued that another limitation of the present study was the possibility of a ceiling effect: if patients’ drug problems were already at their maximum, it would be impossible to detect contributions from cannabis use. Mathematically, this was not the case. (For example, at posttreatment follow-up, participants reported having experienced drug-related problems on 13.5±0.9 out of the past 30 days, with a median of 5 and a range of 0–30.) It may be instructive to note that in another sample of methadone-maintained patients, ceiling effects did not prevent detection of problems associated with smoking tobacco (McCarthy et al., 2002).