1. Introduction

Despite a benign public perception, Cannabis Use Disorder (CUD) represents a significant public health problem. Cannabis is a widely used substance in the United States with approximately 27.7 million individuals reporting past-month use, and accounting for almost 14% of individuals receiving substance use disorder treatment, according to the 2018 National Survey of Drug Use and Health (Substance Abuse and Mental Health Services Administration (SAMHSA), 2019). While psychotherapeutic approaches have been extensively studied to treat CUD, the therapeutic benefit of these interventions do not work for many and are not easily accessible (Gates et al., 2016; Levesque and Le Foll, 2018).

Numerous medications, with varying mechanisms of action, have been tested as potential treatments for CUD. Many of the studies have been conducted in laboratory settings among non-treatment seekers (Balter et al., 2014; Brezing and Levin, 2018). Using a placebo-controlled design, medications in the laboratory are considered promising if they have been more likely to show a reduction in the subjective effects of marijuana, marijuana withdrawal symptoms or self-administration of marijuana after enforced abstinence or recent use (Balter et al., 2014). Often the positive results in the laboratory are not replicated when outpatient clinical treatment trials are conducted (Brezing and Levin, 2018; Nielsen et al., 2019). Part of this may be due to the choice in the outpatient outcome measure. As noted by Lee et al. (2019), the majority of outpatient treatment trials have focused on abstinence. While those with greater marijuana problem severity are more likely to state abstinence as a goal, a substantial minority of those entering treatment will have moderation as a preferred goal. Moreover, treatment outcome best aligns with the patient’s stated goal (Lozano et al., 2006). It may be unrealistic to expect abstinence among individuals who do not have abstinence as their initial goal of treatment or change their minds as treatment progresses (Hughes et al., 2008; Hughes et al., 2016).

One relatively large trial (n=116), conducted in adolescents with CUD, found that n-acetylcysteine was superior to placebo in promoting abstinence as the trial progressed (Gray et al., 2012). However, unlike other larger trials (n>100) that had abstinence as the primary outcome with escalating incentives targeting study adherence (Levin et al., 2011; Levin et al., 2013; Levin et al., 2016; McRae-Clark et al., 2015), for the Gray et al. study (2012) the medication was combined with a contingency management strategy that provided incentives for negative urine toxicologies for marijuana. While this approach may have enhanced the likelihood of detecting a medication effect by improving treatment adherence, when applied to adults with CUD, n-acetylcysteine did no better than placebo in producing abstinence (Gray et al., 2017).

This leads to the question of whether abstinence is a necessary goal of treatment. Conceptually, there are multiple possible targets for CUD including withdrawal, craving, attenuations of reward, reduction in use, and abstinence. The alcohol treatment literature often uses non-abstinent outcomes such as reduction in days of use and no heavy drinking use days as outcomes since they are associated with improved psychosocial functioning and reduced morbidity and mortality (Kline-Simon et al., 2013; Lee et al., 2019); however, unlike alcohol, reduction in marijuana use has not been clearly shown to produce psychosocial or medical benefits.

However, three recently published prominent studies have reported non-abstinent outcomes as their main outcome measures. A clinical trial conducted by D’Souza et al. (2019) evaluated a fatty acid amide hydrolase (FAAH) inhibitor (PF-04457845), as an agent to treat cannabis withdrawal and reduce cannabis use. The authors found that compared to placebo, PF-04457845 was superior in reducing symptoms of cannabis withdrawal, lowering self-reported cannabis use at 4 weeks (measured in joints/day), and having lower urinary marijuana metabolite concentrations. Two other studies compared nabiximols (a combination medication of THC and cannabidiol) to placebo. One study found that nabiximols had a greater number of days abstinent compared to placebo but on a secondary outcome of 1 or more 4-week periods of continuous abstinence the two groups were not significantly different (Lintzeris et al., 2019). The other study found that cannabidiol, at either 400 mg or 800 mg a day, was associated with lower urinary metabolites and slightly less days of use per week (<0.5 days/week) (Freeman et al., 2020).

In a recent systematic review of measures and outcome used in treatments trials for CUD, Lee et al. (2019) note that abstinence was an outcome in 67% of trials, although 76% had reduction in frequency of use and 45% had reduction in quantity of use as a self-reported outcome. For the medication trials in which a primary outcome was reported, abstinence was the primary outcome for most studies. It may be reasonable to reconsider whether abstinence should be the primary outcome in CUD clinical trials.

Our group conducted two single site trials assessing the efficacy of dronabinol (DRO) or the combination of lofexidine and dronabinol (LFD) using a placebo-controlled, randomized design (Levin et al., 2011; Levin et al., 2016). Because DRO is a synthetic form of delta-9- tetrahydrocannabinol, the naturally occurring pharmacologically active component of marijuana, it was tested on the hypothesis that, similar to buprenorphine for opioid use disorder, it would act as an “agonist” and promote abstinence. When dronabinol was not shown to impact abstinence (Levin et al. 2011), another study was conducted evaluating LFD (Levin et al., 2016). This was based on the hypothesis that lofexidine, an alpha-2- noradrenergic agonist, would mitigate cannabis withdrawal symptoms, similar to its effect on opioid withdrawal and provide complementary pharmacologic properties to dronabinol to reduce use and facilitate abstinence.

The primary outcome, abstinence, was negative for both studies. The secondary outcome measure, reduction in overall days/week of use or weekly averaged amount (as measured in dollars or grams) of use were not different for either treatment arm for the DRO trial or the LFD trial. However, neither of these trials were analyzed using the approach for our most recent randomized trial comparing quetiapine (QTP) to placebo (Mariani et al., 2020). For the recently published QTP study, similar to the earlier ones, participants were required to be daily or near daily users. QTP has a complex mechanism of action including acting as an antagonist at several serotonin, histamine, adrenergic and dopamine receptors (Nemeroff et al., 2002). Clinically, it helps with anxiety and mood stabilization and is sedating. It was hypothesized that these effects may counter some of the commonly observed cannabis withdrawal symptoms and lead to reduction in use (Mariani et al. 2014; 2020).

For the QTP study we chose reduction in days of use rather than abstinence based on an open-label pilot study results which showed that participants reduced their amount of cannabis use and number of days per week of use, with very few achieving continuous abstinence (Mariani et al., 2014). The decision to use change in days of use each week rather than a quantity of use was based on two factors; 1) the amount of use is hard to reliably assess and 2) dollars of use can vary considerably based on the potency. For all three studies, the number of days per week of use across all visits followed a bimodal or U-shaped distribution, with more participants at 0 or 7 days of use, and fewer in between. Therefore, individuals were a priori categorized into three clinically meaningful groups: light use (0–1 day a week), moderate use (2–4 days a week) and heavy use (5–7 days a week). This approach is supported by findings showing that individuals placed into these categories have significantly different levels of cannabis-related problems (Asbridge et al., 2014). Notably, compared to those receiving placebo, those receiving QTP were more likely to belong to the moderate use group compared to heavy use, with each week in the study, particularly at the halfway point of the study (week 5). Based on these findings, we were interested in conducting secondary analyses to determine if this pattern would also be observed in our two prior medication trials targeting CUD.

2. Methods

2.1. Sample and study design

Details regarding recruitment, screening, inclusion and exclusion criteria, study design and CONSORT Diagrams for the DRO, LFD and QTP trials have been previously reported (Levin et al., 2011; Levin et al., 2016; Mariani et al., 2020). All participants were seeking outpatient treatment for cannabis use and for both the DRO and LFD trials participants met criteria for current cannabis dependence based on the Structured Clinical Interview (SCID) for Diagnostic and Statistical Manual of Mental Disorders- Axis I disorders DSM-IV (APA, 1994; First et al., 1995). Participants in the QTP trial met criteria for current cannabis dependence based on the MINI-Neuropsychiatric (Sheehan et al., 1998) for DSM-IV criteria (APA, 1994).

For both the DRO and LFD trials participants had to report using ≥ 5 days/week during the prior 28 days to enrolling in the study. In the QTP trial participants had to report using an average of 5 days or more/week over the prior 28 days to enrollment in the trial. Baseline characteristics of participants are described elsewhere in detail (Levin et al., 2011; Levin et al., 2016; Mariani et al., 2020). All participants in the three trials were treated at the Substance Treatment and Research Service (STARS) of Columbia University/ New York State Psychiatric Institute. Study enrollment for the DRO trial occurred from March 2005 through November 2009; enrollment for the LFD trial occurred from December 2009 through May 2014; and enrollment for the QTP trial occurred from October 2012 through February 2017.

The DRO study was a single-site, randomized, double-blind, parallel-group, clinical trial comparing placebo to dronabinol, with a maximum targeted dose of 20 mg BID. Of the 184 who were enrolled, 156 participants were randomized to receive dronabinol (n=79; 50.6%) or PBO (n=77; 49.4%) up to study week 8 (prior to dose taper and placebo lead-out) (Levin et al., 2011). The LFD study was a single-site, randomized, double-blind, parallel-group, clinical trial comparing placebo to dronabinol plus lofexidine, with a maximum targeted dose of 20 mg three times a day and 0.6 mg three times a day respectively. Of the 156 participants enrolled in the double-blind study, 122 participants were randomized to receive either active medication (dronabinol and lofexidine) (n=61; 50.0%) or PBO (n=61; 50.0%) for up to study week 8 (prior to dose taper and placebo lead-out) (Levin et al., 2016). All participants in both trials received manualized motivational enhancement and weekly cognitive behavioral/relapse prevention therapy over the course of the trial.

The QTP study was a single-site, randomized, double-blind, parallel-group, clinical trial comparing placebo to quetiapine (up to a maximum dose of 300 mg/daily). Of the 130 participants enrolled in the double-blind study, 130 participants were randomized to receive either active medication (quetiapine) (n=66; 50.7%) or PBO (n=64; 49.2%) for up to study week 12 (prior to dose taper) (Mariani et al., 2020). The psychosocial intervention utilized for the QTP trial was a manual-guided supportive behavioral treatment session (Pettinati et al., 2005) based on Medical Management used for Project COMBINE (Anton et al., 2006) and modified for marijuana dependence. Sessions with the research psychiatrist were weekly and meant to promote compliance with study medication and abstinence from marijuana.

2.2. Measures

2.2.1. Cannabis Use

The timeline follow-back (TLFB) assessment (Litten and Allen, 1992) modified for cannabis (Mariani et al., 2011) was used to assess participants’ cannabis use at twice weekly visits. Details of this procedure can be found in prior publications by our group (Levin et al., 2011; Levin et al., 2016; Mariani et al., 2011, Mariani et al., 2020). A strong association had previously been found between TLFB and urine drug screens in the placebo arm of the DRO study (Levin et al., 2011) thus supporting the use of the TLFB as a reliable method to measure cannabis use.

2.2.2. Quality of Life

For the LFD study, the Quality of Life Enjoyment and Satisfaction Questionnaire-short form (QLES-Q-SF) was assessed at baseline and end of study (Endicott et al., 1993).

2.3. Statistical analysis

For all three studies, the number of days per week of use across all available time points, followed a bimodal or U-shaped distribution, with more participants at 0 or 7 days of use, and fewer in between. Therefore, the outcome of cannabis use days per week was a priori categorized into 3 clinically meaningful groups: heavy use (defined as 5–7 use days/week), moderate use (defined as 2–4 use days/week) and light use (defined as 0–1 use day/week). For subjects missing some days of TLFB data, the following rules were used to create the categorical cannabis use outcome: 1) for subjects with less than 3 self-reported days in a week, the corresponding week was denoted as missing; 2) for subjects with 3–5 self-reported days in a week, the missing data were imputed using the percentage of self-reported abstinent days per that week; and 3) for subjects with 6 self-reported days in a week the outcome category was determined when possible (e.g., if all 6 self-reported days were abstinent, the week was categorized as light use), otherwise the missing days were imputed as in step 2. For participants who dropped out of the study, the weeks after their last week in the study were considered to be missing.

The statistical models used for all three studies were multinomial logistic regression to accommodate the 3-category outcome. Ordinal logistic regression was considered but not used because the proportional odds assumption was violated. The effect of treatment over time was modeled using a time*treatment interaction term, where time was assessed weekly and analyzed as a continuous variable, while adjusting for age, sex, and baseline marijuana use (measured in dollars spent). The model for the QTP study also included baseline presence of co-occurring mood/anxiety disorders as a covariate. This multinomial logistic regression model generates multiple odds ratios (OR) for each binary predictor that compare the odds of achieving each category of the outcome with the reference group (heavy use). Therefore, the 3-category outcome corresponds to two ORs for each binary predictor. For example, the effect of binary treatment on the 3-category outcome in a certain week is expressed as 1) the odds of light use compared to heavy use among those who were in treatment group compared to PBO, denoted as “OR_L-H”; and 2) the odds of moderate use compared to heavy use among those who were in treatment group compared to PBO, denoted as “OR_M-H”. Each OR was tested using a Wald Х² test. These odds ratios and corresponding 95% confidence intervals (95% CI) were computed for each week of the study.

To assess the effect of the covariates, the same analyses described above were also repeated in two ways: (1) without any covariates and (2) with only the covariates collected across all three studies, i.e., the covariate of co-occurring mood/anxiety was excluded from the QTP analysis. Additionally, a sensitivity analysis was also performed to assess the effect of dropouts, where the weeks after dropout was considered as belonging to the heavy use group.

In the LFD study (the only study with administered quality of life scale), the association between use categories and quality of life (measured by Q-LES-Q) was explored. The proportion of heavy use weeks over the course of the LFD study were calculated for each participant and correlated using a simple linear regression with Q-LES-Q score measured for each participant at the end of the study.

All models were analyzed in SAS® 9.4 using PROC LOGISTIC and all graphs were produced using R version 3.6.3. All hypothesis tests were two-sided with level of significance 5%.

3. Results

3.1. Summary results

The observed proportions of participants in heavy, moderate, and light use categories by week and treatment group are shown in Figure 1 with the lightest color denoting light use and the darkest color denoting heavy use.

Across the three trials, there was no significant overall time-by-treatment interaction (QTP: p = .06; DRO: p = .15; LFD: p = .21), suggesting no significant differences in the longitudinal pattern of use over time between treatment groups, while adjusted by other covariates. However, all three studies showed similar patterns of increasing odds of moderate compared to heavy use among the treatment group compared to the placebo group. There were no repeated patterns of association between treatments and light compared to heavy use (see Table 1a, 1b, and 1c for details).

3.1.1. Moderate use compared to heavy use

In all three trials, similar patterns of association between moderate compared to heavy use were observed (see Figure 1). In the treatment arm, the odds of moderate use compared to heavy use were significantly higher than those in placebo, starting from around the midpoint of each trial.

Specifically, in the 12-week long QTP study, during weeks 1–4 the effect of quetiapine on moderate compared to heavy use was not significantly different from the effect of PBO. However, starting from week 5, significant differences emerge and the quetiapine group becomes significantly associated with higher odds of moderate use (Mariani et al. 2020). At week 5, the odds of moderate use compared to heavy use for the quetiapine group were 1.56 times the odds of moderate use compared to heavy use in the PBO group (OR_M-H = 1.56; 95% CI: 1.11, 2.20; p = .0102, see Table 1a). At week 12, the OR_M-Hincreased to 3.30 (95% CI: 1.68, 6.47; p = .0005).

In the 8-week long DRO study, during weeks 1–2 the effect of dronabinol on moderate compared to heavy use was not significantly different from the effect of PBO. However, starting from week 3, the dronabinol group is significantly associated with higher odds of moderate use compared to PBO (see Table 1b). At week 3, the OR_M-H was 1.47 (95% CI: 1.01, 2.12; p = .042); at the end of the study, week 8, the OR_M-H increased to 2.17 (95% CI: 1.12, 4.17; p = .021).

In the 8-week long LFD study, during weeks 1–4, the effect of LFD on moderate compared to heavy use was not significantly different from the effect of PBO. But during weeks 5–8, the lofexidine and dronabinol group was significantly associated with higher odds of moderate use compared to PBO (see Table 1c). At week 5, the OR_M-H was 1.66 (95% CI: 1.03, 2.69; p = .0371); at week 8 the OR_M-H increased to 2.79 (95% CI: 1.13, 6.89; p = .0262).

3.1.2. Light use compared to heavy use

There was no repeated pattern of association between treatments in light use compared to heavy use across these three analyses (see Tables 1a, 1b, 1c). In the QTP study, the odds of light compared to heavy use was significantly lower for those in the quetiapine group during weeks 1–5 only. Whereas in the LFD study, the odds of light compared to heavy use was significantly higher in the LFD group later in the study, during weeks 4–7. No significant treatment effect on light compared to heavy use was seen in the DRO study.

3.1.3. Sensitivity analyses of dropouts and covariates

Removing all covariates from the analyses or keeping only those covariates that were collected in all three studies did not meaningfully change the original results.

The results of sensitivity analysis in which dropouts were treated as heavy users were also not meaningfully different from the original results presented above. All patterns of use described above were similar.

3.2. Proportion of use categories and quality of life

For the LFD study, the only study where the QLESQ-SF assessment was conducted, there was an association between proportion of heavy use weeks and Q-LES-Q score at week 12 (p = .0079): for a decrease of 10% in the proportion of heavy use weeks, the Q-LES-Q score increased, on average, by 0.87 points.

4. Discussion

Earlier analyses of two published trials did not find that abstinence or overall reduction in days of use were greater among those on active treatment compared to the placebo arm (Levin et al., 2011; Levin et al., 2016). However, conducting secondary analyses using an approach conducted with a recently completed trial (comparing quetiapine to placebo, Mariani et al., 2020), found a similar pattern of results. Specifically, for all three studies, starting at the midpoint of each trial the odds of moderate compared to heavy use were significantly higher in the treatment arm. This pattern was not consistently observed in the odds of light compared to heavy use across treatment groups.

The critical question is why this observation occurred. While most patients will report that abstinence is their goal when they enter treatment (Lozano et al. 2006), this often changes over time (Hughes et al. 2008; 2016). While we did not formally evaluate for motivation to become abstinent for two of the trials (Levin et al. 2011; 2016), our clinical observations were that the goal of abstinence is not tightly held, particularly if a participant is satisfied with a lower level of use. For the QTP trial, we began to routinely evaluate patients’ goals throughout treatment. In the QTP study, when asked to rate what would be considered “treatment success” on a scale of 1–10, with 1 being no reduction and 10 being complete abstinence, the majority (69%, 90/130) of the participants considered some reduction (rating between 3–9) to be a success, compared to only a third of participants rating complete abstinence as treatment success.

However, regardless of motivation or baseline treatment goals, unless there is a more powerful agonist, a negative allosteric modulator of the CB1, or an antagonist that is long-lasting and safe, it may be difficult for individuals to achieve full abstinence. Further, light use (which allows 1 day/week) may also substantially be more difficult to achieve than moderate (2–4 days/week) use, unless we develop more powerful (and safe) pharmacologic interventions.

Notably, in two of the trials we looked at reduction in use based on reduction in overall days/week of use and weekly averaged amount (as measured in dollars or grams) and found no significant reduction in overall use; whereas when we categorized patients’ use patterns into light/moderate/heavy use groups we found suggestions of group differences. There are several possible explanations regarding this potential discrepancy. First, it may be harder for participants to reliably report amount of use compared to identifying each day as a nonuse/use day. Second, participants in the placebo arm might compensate for less amount of use by converting to greater potency of marijuana use. Finally, because the distribution of use days across all three studies was bimodal, with more subjects at the extremes, i.e., 0 use days or 7 use days in any given week, using averages may not be meaningful, rather the bimodality suggests the presence of different groups of individuals and categorization may allow for a better understanding of changes in cannabis use.

What remains an important clinical question is whether the change from a heavy to moderate use pattern is clinically meaningful and a reasonable outcome. As noted by two recent reviews, there are no clear-cut valid and reliable instruments to determine clinical outcomes for CUD (Lee et al., 2019; Loflin et al., 2020). To date, the most common measures used to assess outcome are self-reported use, often determined by timeline follow-back alone or in conjunction with urine toxicology data. However, even with these commonly used measures, the way they are utilized is quite variable. Unlike the CUD treatment literature, the alcohol and tobacco literature have established greater consensus. Typically, prolonged abstinence is the preferred outcome since there is no safe level of tobacco smoking (Hughes et al., 2003; Lee et al., 2019). With regards to alcohol consumption, Lee et al. (2019) note that several studies have found that there are positive short- and long- term effects on psychosocial functioning with the eradication of heavy drinking days (Kline-Simon et al., 2013; Kline-Simon et al., 2017; Witkiewitz et al., 2017) that provide support for mild or non-risky use as an alcohol treatment outcome.

While chronic heavy alcohol use can cause various medical comorbidities, this is less clear for chronic cannabis use. There are data supporting that chronic cannabis use produces psychiatric symptoms and cognitive impairments (Andrade et al., 2016). Yet, it remains an empirical question whether reducing cannabis use would improve psychosocial functioning and psychiatric symptoms among those with such symptoms (Loflin et al., 2020). Perhaps for this reason, supplementing change in cannabis use with reduction in DSM-5 CUD symptoms might make sense (Lee et al., 2019). The limitation of this approach is that some individuals entering treatment meet criteria for mild to moderate CUD with only 2–5 symptoms, thus generating a potential floor effect when trying to detect efficacy (Hasin et al. 2016); although the majority of individuals entering CUD treatment have severe symptoms (>6). With greater acceptance of cannabis as a medicinal agent and more widespread legalization for recreational use, patients with regular cannabis use, even those entering treatment, may be less likely to endorse 6+ symptoms consistent with severe CUD. Also, using DSM-5 CUD symptoms as an outcome measure requires an awareness of how the treatment has changed the patient’s loss of control, harmful impact on social and occupational functioning, and physical dependence. Recent survey data suggest that Americans view cannabis as less harmful than a decade ago (SAMHSA, NSDUH, 2019). This may have the unexpected effect of having patients less likely to endorse DSM5 CUD symptoms, even among those entering treatment. Given these issues, it makes practical sense to use a measure of frequency of cannabis use as a treatment outcome. Reduced frequency of use/week, if it is associated with other psychosocial improvements, might be a reasonable goal.

For the QTP trial (Mariani et al., 2020), the rationale was based on our clinical experience that daily or near daily users would have greater difficulties than moderate or infrequent users. Notably, this approach was examined by Asbridge et al. (2014) and they found that near daily/daily users were found to have greater cannabis-related problems and total score on the ASSIST (the alcohol, smoking and substance involvement screening test WHO; Asbridge et al., 2014) than less frequent users (<5 days/week). Similarly, categorizing individuals into those who used greater amounts per day (2 or more joints on days of use) was associated with having greater cannabis problems compared to those who used fewer joints (1 or less joints on days of use); however, the rationale behind the selection of these criteria for grouping was not given.

Findings from a secondary analysis of our LFD clinical trial (Brezing et al., 2018) suggest reduction in cannabis use is associated with improved quality of life. For this study we looked at the LFD trial again and found that reduction in proportion of heavy use weeks was also associated with improved quality of life, however, we cannot say if cannabis related problems/DSM symptomatology were related to either of these changes in use patterns or improved quality of life. While we cannot conclude from this secondary analysis what the best primary outcome for a cannabis treatment trial should be, we would contend that reduction in use might be considered for future trials, with improvement in quality of life/improved functioning and less cannabis-related problems as secondary outcomes. However, this does not address how reduction in use would be defined. This analysis suggests one way to measure quality of life, but without more data it is hard to conclude that it is superior to another approach. It is notable that the medications that looked promising in the human laboratory, were not so in the outpatient clinical treatment trials when abstinence was used as an outcome measure. Yet, the laboratory findings translated to positive results in the outpatient setting when categorical reduction in frequency of use was applied. It may be that for early phase II clinical treatment trials, abstinence may be too high a hurdle, and reduction in use is a more appropriate primary outcome measure.

The weekly contrasts reported in this paper were pre-specified a priori, regardless of the overall time by treatment interaction effect. There were group differences in the odds of going from heavy use to light use from weeks 1–5 in the QTP trial and weeks 4–7 of the LFD trial. However, these differences were not maintained as the trials progressed. While this early, substantial improvement is noteworthy, without extending the study length it is hard to determine whether this early effect is spurious or predictive of a future return to this robust reduction in use for those maintained on the QTP or LFD. Similarly, our positive results in the odds of going from heavy use to moderate use at the end of the three trials might be spurious, despite similar findings for all three trials.

Additionally, the sensitivity analyses treating dropouts as heavy users showed no meaningful differences from the original results presented above, suggesting that dropouts did not bias the main findings. Other sensitivity analyses were performed to assess the effect of covariates in the analyses. Removing all covariates from the analyses or keeping only covariates that were in all three studies did not affect the original results.

A limitation of this study is that all of the treatment conditions relied on self-report. While self-report is a standard measure used to evaluate reduction in use, there may be differential reporting of cannabis use based on treatment arm when there are differences in side effects. Mitigating this are our prior findings in which amount of use and overall days of use did not differ across treatment arms (Levin et al. 2011; 2016).

Another clear limitation of this paper is that it is a secondary analysis. However, we would contend that this secondary analysis provides support along with prior reviews (Lee et al., 2019; Loflin et al., 2020) that further research into alternative outcome measures is reasonable for cannabis treatment trials.

5. Conclusion

In summary, this secondary analysis explores an alternate way of examining outcomes in the treatment of CUD. In the current environment, abstinence as an outcome in the treatment of CUD is not a consistent goal of patients nor is it necessarily the only outcome associated with clinical or functional improvement. Medication trials that have previously been deemed “negative” as they relate to abstinence may warrant further analysis regarding their effectiveness in reducing cannabis use. Future research is needed to determine the clinical relevance of the outcome used for this paper as well as other reduction in use outcomes and their clinical and functional correlates.

Introduction

Cannabis Use Disorder (CUD) represents a significant public health concern. Many individuals use cannabis, and a considerable number seek treatment for CUD. While talk therapies have been extensively studied for CUD, these treatments often do not work for everyone and are not always easy to access.

Various medications have been tested as potential treatments for CUD. Many studies were conducted in laboratory settings. Positive results from laboratory studies, such as reduced subjective effects or withdrawal symptoms, often do not translate to success in outpatient clinical trials. This may be partly because outpatient trials often focus on complete abstinence as a primary goal. However, some individuals entering treatment aim for moderation rather than abstinence. Treatment outcomes tend to be more successful when they align with a patient's stated goals. Expecting complete abstinence might be unrealistic for those who do not set it as their initial aim.

One study with adolescents found that n-acetylcysteine helped promote abstinence, but this was in combination with incentives for staying abstinent. When the same medication was tested in adults with CUD, it did not show better results than a placebo in achieving abstinence. This raises the question of whether complete abstinence is always the necessary goal for CUD treatment. In alcohol treatment, non-abstinent goals, such as reducing heavy drinking days, are often used as outcomes because they are linked to improved health and social functioning. For cannabis, it is not yet clear if reducing use alone leads to similar benefits.

Recently, some notable studies have used non-abstinent outcomes. One clinical trial found that a specific medication reduced cannabis withdrawal symptoms and self-reported cannabis use. Other studies investigated medications like nabiximols and cannabidiol, finding some reduction in cannabis use or its metabolites, though not always leading to continuous abstinence. A systematic review of CUD treatment trials showed that while most studies used abstinence as their main outcome, many also measured reductions in frequency or quantity of use. This suggests it may be reasonable to reconsider whether abstinence should always be the primary outcome in CUD studies.

Previous trials conducted by a research group evaluated dronabinol alone or in combination with lofexidine for CUD treatment. These studies primarily aimed for abstinence, but this outcome was not achieved. Other measures, like overall reduction in days or amount of use, also showed no difference between active treatment and placebo. However, a more recent trial comparing quetiapine to placebo chose to measure reduction in days of use, based on earlier pilot study results. This quetiapine study found that participants on the active medication were more likely to move from heavy use to moderate use. This positive finding prompted a re-analysis of the two earlier medication trials using the same categorization of use patterns.

Methods

Details of participant recruitment, screening, and study design for the dronabinol (DRO), lofexidine and dronabinol (LFD), and quetiapine (QTP) trials have been previously published. All participants sought outpatient treatment for cannabis use. Participants in the DRO and LFD trials met criteria for cannabis dependence using DSM-IV. QTP trial participants also met criteria for cannabis dependence. Across all three studies, participants were required to report using cannabis at least 5 days per week during the month before enrollment. All treatments were provided at the Substance Treatment and Research Service of Columbia University/New York State Psychiatric Institute between 2005 and 2017.

The DRO study was a randomized, double-blind trial comparing dronabinol (up to 20 mg twice daily) to placebo. Out of 184 enrolled, 156 were randomized. The LFD study was a similar trial comparing a combination of dronabinol and lofexidine to placebo, with 122 participants randomized from 156 enrolled. Both DRO and LFD trials included manualized motivational enhancement and weekly cognitive behavioral therapy. The QTP study was also a randomized, double-blind trial comparing quetiapine (up to 300 mg daily) to placebo, with 130 participants randomized. The QTP trial included manual-guided supportive behavioral treatment sessions aimed at promoting medication compliance and abstinence.

Cannabis use was assessed at twice-weekly visits using a modified Timeline Follow-Back (TLFB) assessment. This method has been supported by findings showing a strong link between TLFB reports and urine drug screen results in previous studies. For the LFD study only, the Quality of Life Enjoyment and Satisfaction Questionnaire-short form (QLES-Q-SF) was used at the beginning and end of the study.

For all three studies, weekly cannabis use days showed a bimodal distribution, meaning participants often reported either no use or daily use. Therefore, cannabis use was categorized into three groups: heavy use (5–7 days/week), moderate use (2–4 days/week), and light use (0–1 day/week). Rules were applied to handle missing data for some weeks. Participants who left the study had their remaining weeks considered missing. Multinomial logistic regression models were used for analysis, as this approach is suitable for outcomes with more than two categories. These models evaluated the effect of treatment over time, adjusting for factors such as age, sex, and baseline cannabis use. For the QTP study, baseline mood/anxiety disorders were also included as a covariate. The analysis generated odds ratios comparing the likelihood of being in the light use group versus heavy use, and the moderate use group versus heavy use, for the treatment group compared to the placebo group. Sensitivity analyses were conducted to see if results changed when covariates were removed or if dropouts were assumed to be heavy users. For the LFD study, the relationship between the proportion of heavy use weeks and quality of life scores at the end of the study was examined using linear regression.

Results

Overall, no significant differences were observed in the long-term pattern of cannabis use between treatment groups and placebo across the three trials. However, all three studies showed similar trends: treatment groups had increasing odds of being in the moderate use category compared to the heavy use category. This pattern was not consistently observed for light use compared to heavy use.

For all three trials, a similar association emerged where the odds of moderate use compared to heavy use were significantly higher in the active treatment groups compared to placebo, typically starting around the midpoint of each trial. In the 12-week QTP study, significant differences appeared from week 5, with the quetiapine group showing increasingly higher odds of moderate use compared to heavy use by week 12. Similarly, in the 8-week DRO study, significant differences for moderate use emerged from week 3, continuing to increase by the end of the study. The 8-week LFD study also showed that from week 5 to week 8, the lofexidine and dronabinol group had significantly higher odds of moderate use compared to heavy use.

No consistent pattern was found for light use compared to heavy use across the three studies. In the QTP study, the odds of light use were lower for the quetiapine group early in the study. Conversely, in the LFD study, the odds of light use were significantly higher in the LFD group later in the trial. The DRO study showed no significant treatment effect on light use. Sensitivity analyses, which involved removing covariates or classifying participants who dropped out as heavy users, did not significantly alter the main findings. In the LFD study, which measured quality of life, a decrease in the proportion of heavy use weeks was associated with an improved quality of life score at the end of the study.

Discussion

Earlier analyses did not find greater abstinence or overall reduction in cannabis use among those on active treatment compared to placebo. However, this secondary analysis, using a categorization approach, found a similar pattern across all three studies: active treatment groups showed significantly higher odds of moderate cannabis use compared to heavy use, typically from the midpoint of each trial. This raises questions about what constitutes a successful treatment outcome. Many patients initially aim for abstinence but often change their goal to moderation, and treatment success often aligns with patient goals.

Achieving complete abstinence or even very light use may be challenging without more powerful pharmacological interventions. Furthermore, categorizing use into heavy, moderate, and light groups may provide a more meaningful understanding of changes in use patterns than using averages, especially since cannabis use often shows a bimodal distribution. This could be due to differences in the reliability of self-reported cannabis amount versus use days, or possible compensation by placebo groups using more potent cannabis.

An important clinical question is whether a shift from heavy to moderate cannabis use is clinically meaningful. Unlike alcohol and tobacco treatment literature, where clear outcomes are established, there are no clear, validated measures for CUD clinical outcomes. While chronic heavy cannabis use is linked to psychiatric symptoms and cognitive issues, it is not yet empirically proven that reducing cannabis use improves psychosocial functioning or psychiatric symptoms. However, prior research and the current analysis suggest that reducing heavy cannabis use is associated with improved quality of life. Given these complexities, using frequency of cannabis use as a treatment outcome, perhaps alongside symptom reduction, is a practical approach.

This analysis suggests that reduction in use could be a reasonable primary outcome for future CUD trials, with improvements in quality of life and functioning as secondary outcomes. It is notable that medications showing promise in laboratory settings yielded positive results in outpatient trials when categorical reduction in use was applied, whereas they did not when abstinence was the primary outcome. For early-phase clinical trials, reduction in use might be a more appropriate and achievable primary outcome than complete abstinence. A limitation of this study is its reliance on self-reported cannabis use, though prior findings mitigate this. The study is a secondary analysis, but it supports the need for further research into alternative outcome measures for cannabis treatment trials.

Conclusion

This secondary analysis explores an alternative approach to examining outcomes in Cannabis Use Disorder (CUD) treatment. In the current context, complete abstinence as a treatment outcome for CUD is not always the patient's consistent goal, nor is it necessarily the only outcome linked to clinical or functional improvement. Medication trials previously considered "negative" based on abstinence outcomes may warrant re-evaluation for their effectiveness in reducing cannabis use. Future research is needed to determine the clinical relevance of reduction in use as an outcome measure, as well as its association with clinical and functional improvements.

Introduction

Cannabis Use Disorder (CUD) represents a significant public health issue, despite a generally positive public view of cannabis. Many individuals in the United States use cannabis, and CUD accounts for a notable percentage of those receiving treatment for substance use disorders. While various psychological treatments have been studied for CUD, their benefits are often not widespread or easily accessible.

Numerous medications, working in different ways, have been tested as potential treatments for CUD. Many of these studies were conducted in laboratory settings with participants who were not actively seeking treatment. In these lab settings, medications are considered promising if they reduce the subjective effects of marijuana, lessen withdrawal symptoms, or decrease self-administration after a period of abstinence or recent use. However, positive results from lab settings are often not replicated in outpatient clinical trials. This discrepancy may partly stem from how success is measured in outpatient studies. Most outpatient trials have focused on complete abstinence, even though many individuals entering treatment may prefer to reduce their use rather than stop entirely. Treatment outcomes tend to be better when they align with a patient's stated goals.

One relatively large trial involving adolescents with CUD found that a medication called N-acetylcysteine was more effective than a placebo in promoting abstinence over time. However, this study combined the medication with incentives for negative urine tests. When this medication was tested in adults with CUD, it was not more effective than a placebo in producing abstinence.

These findings raise the question of whether complete abstinence is always a necessary treatment goal. CUD treatment could potentially target various outcomes, such as reducing withdrawal symptoms, cravings, or overall cannabis use. In the context of alcohol treatment, non-abstinence outcomes like reducing heavy drinking days are often used because they are linked to better social functioning and health. For cannabis, however, it is less clear whether simply reducing use leads to similar psychosocial or medical benefits.

Despite this, three recent significant studies have used non-abstinence outcomes as their main measures. One clinical trial found that a medication called a fatty acid amide hydrolase (FAAH) inhibitor was better than a placebo at reducing cannabis withdrawal symptoms and self-reported use. Two other studies evaluated nabiximols (a combination of THC and cannabidiol); one found it led to more days of abstinence, while the other showed that cannabidiol was associated with lower cannabis markers and slightly fewer days of use per week.

Methods

This analysis examined data from three previously conducted, randomized, double-blind, placebo-controlled clinical trials for individuals seeking outpatient treatment for cannabis use. All participants met criteria for current cannabis dependence and reported using cannabis frequently (at least 5 days a week) before enrolling. The studies took place at the Substance Treatment and Research Service (STARS) of Columbia University/New York State Psychiatric Institute between 2005 and 2017.

The first study compared dronabinol, a synthetic form of THC, to a placebo. Participants were randomized to receive either dronabinol or placebo for up to eight weeks. The second study compared a combination of dronabinol and lofexidine (a medication known to reduce opioid withdrawal symptoms) to a placebo, also for up to eight weeks. Participants in both these trials also received weekly motivational enhancement and cognitive behavioral therapy. The third study compared quetiapine to a placebo for up to 12 weeks. Participants in this trial received weekly supportive behavioral treatment.

Cannabis use was assessed at twice-weekly visits using a modified Timeline Follow-Back (TLFB) assessment, which has been shown to reliably measure cannabis use. For all three studies, weekly cannabis use days often showed a bimodal pattern, with many participants reporting either zero or seven days of use, and fewer in between. Because of this, weekly cannabis use was categorized into three groups: heavy use (5–7 days/week), moderate use (2–4 days/week), and light use (0–1 day/week). Statistical analysis used multinomial logistic regression to compare the odds of being in the light or moderate use category versus the heavy use category for the treatment groups compared to placebo, over time. The LFD study also assessed quality of life using a specific questionnaire.

Results

Overall, across the three trials, there was no significant difference in the general pattern of cannabis use over time between the active treatment and placebo groups. However, all three studies showed a similar trend: the odds of moderate use compared to heavy use increased significantly in the treatment group relative to the placebo group. This pattern was not consistently observed for light use compared to heavy use across the treatment groups.

Specifically, for all three trials, starting around the midpoint of each study, individuals receiving active medication were significantly more likely to shift from heavy to moderate cannabis use than those on placebo. In the 12-week quetiapine study, this shift became significant from week 5 onwards, with the odds of moderate use increasing more than threefold by week 12 compared to placebo. In the 8-week dronabinol study, the shift to moderate use became significant from week 3, nearly doubling by week 8. Similarly, in the 8-week dronabinol and lofexidine study, this significant shift began in week 5 and nearly tripled by week 8.

Regarding light use compared to heavy use, no consistent pattern was observed across the three analyses. The quetiapine study showed lower odds of light use early on, while the dronabinol and lofexidine study showed higher odds of light use later in the study. The dronabinol study showed no significant effect on light use. Sensitivity analyses, which included treating dropouts as heavy users and adjusting for different sets of covariates, did not significantly change these main findings.

In the dronabinol and lofexidine study, the only trial that assessed quality of life, a decrease in the proportion of heavy use weeks was associated with an improvement in quality of life scores at the end of the study.

Discussion

Previous analyses of two of the included trials indicated no significant improvements in abstinence or overall reduction in cannabis use with active treatment compared to placebo. However, by re-analyzing the data using a categorical approach (dividing use into heavy, moderate, and light), a consistent pattern emerged across all three studies. Starting around the midpoint of each trial, individuals in the active treatment groups were significantly more likely to reduce their use from heavy to moderate levels compared to those receiving placebo. This consistent pattern was not observed for a shift from heavy to light use.

The observed shift from heavy to moderate use raises important questions. While many patients initially state abstinence as their goal, this often changes over time. It may be unrealistic to expect complete abstinence, especially if patients are satisfied with a lower level of use. Achieving light use might also be challenging without more powerful pharmacological interventions. The categorical grouping of cannabis use patterns into heavy, moderate, and light may offer a more meaningful way to track changes than simply looking at average reductions in use. It can be difficult for participants to reliably report exact amounts of cannabis used, and an average might not accurately reflect the bimodal distribution of use, where many people are either abstinent or heavy users.

A crucial clinical question is whether a shift from heavy to moderate use is a meaningful outcome. Unlike alcohol treatment, where reducing heavy drinking clearly leads to health benefits, the benefits of reduced cannabis use on psychosocial functioning and psychiatric symptoms are not as well-established. Future research should explore if reducing cannabis use is associated with improvements in quality of life or a decrease in CUD symptoms. With increasing social acceptance and legalization of cannabis, patients entering treatment may be less likely to report severe CUD symptoms, further highlighting the need for alternative outcome measures like frequency of use.

This secondary analysis suggests that simply reducing the frequency of cannabis use per week, if linked to other psychosocial improvements, could be a reasonable treatment goal. The fact that medications showing promise in lab settings did not lead to abstinence in outpatient trials, but did show positive results when a categorical reduction in frequency was considered, implies that abstinence might be too high a bar for early-phase clinical trials. Reducing use might be a more appropriate primary outcome measure for such studies. While this analysis is a secondary one and relies on self-reported data, it provides further support for exploring and validating alternative outcome measures for cannabis treatment trials.

Conclusion

This secondary analysis explores an alternative way to examine outcomes in the treatment of Cannabis Use Disorder (CUD). In the current environment, complete abstinence as a treatment outcome for CUD is not always the patient's goal, nor is it necessarily the only indicator of clinical or functional improvement. Medication trials that were previously deemed "negative" because they did not lead to abstinence may warrant re-evaluation regarding their effectiveness in reducing cannabis use. Future research is needed to determine the clinical relevance of measuring use reduction, as explored in this paper, and to identify how such reductions correlate with improvements in patients' overall clinical status and daily functioning.

Introduction

Despite a generally harmless public view, Cannabis Use Disorder (CUD) presents a significant public health issue. Cannabis is widely used in the United States, with about 27.7 million individuals reporting use in the past month. It also accounts for nearly 14% of people receiving substance use disorder treatment. While various therapy approaches have been studied for CUD, their benefits do not work for everyone and are not always easy to access.

Many medications have been tested as potential CUD treatments. Much of this research has taken place in laboratory settings with people not actively seeking treatment. In these lab studies, medications are considered promising if they reduce the subjective effects of marijuana, ease withdrawal symptoms, or decrease self-administration after a period of no use. However, positive results from the lab often do not translate to successful outcomes when tested in real-world outpatient clinical trials. Part of this might be due to the focus on complete abstinence as the main goal in many outpatient studies. While individuals with more severe cannabis problems might aim for abstinence, a significant number of people entering treatment prefer to reduce their use. Treatment outcomes tend to be better when they match a patient's stated goal.

One relatively large trial involving adolescents with CUD found that a medication called n-acetylcysteine was more effective than a placebo in promoting abstinence as the study progressed. This study combined the medication with a strategy that provided rewards for negative marijuana drug tests. However, when n-acetylcysteine was tested on adults with CUD, it did not perform better than a placebo in producing abstinence.

This raises the question of whether abstinence is always a necessary goal for CUD treatment. There are several other possible goals, such as reducing withdrawal symptoms, cravings, or overall cannabis use. In the field of alcohol treatment, non-abstinence outcomes, like reducing heavy drinking days, are often used because they are linked to better social functioning and reduced health risks. However, for cannabis, it is less clear whether simply reducing use leads to similar psychosocial or medical benefits.

Despite this, three recent major studies have reported success using non-abstinence outcomes. One clinical trial found that a medication (PF-04457845) reduced cannabis withdrawal symptoms and self-reported cannabis use. Two other studies comparing a combination medication (nabiximols) or cannabidiol to a placebo also reported non-abstinence benefits, such as more days without use or lower cannabis levels in urine. These findings suggest it may be reasonable to reconsider if abstinence should be the only or primary outcome in CUD clinical trials.

Our research group previously conducted two studies assessing dronabinol (DRO) and a combination of lofexidine and dronabinol (LFD) using a placebo-controlled design. These studies primarily aimed for abstinence, but neither found significant success in that regard. However, for a more recent study comparing quetiapine (QTP) to a placebo, a different approach was used. Based on earlier pilot study results, the QTP trial chose reduction in days of use as the main measure of success, as very few participants achieved continuous abstinence. In this QTP study, participants receiving the medication were more likely to move from heavy to moderate cannabis use over time. Based on these findings, we were interested in re-analyzing our two earlier medication trials (DRO and LFD) using this same approach.

Methods

Sample and Study Design

Details regarding how participants were recruited, screened, and designed for the DRO, LFD, and QTP trials have been reported in previous publications. All participants were seeking outpatient treatment for cannabis use. For the DRO and LFD trials, participants met the criteria for current cannabis dependence based on specific diagnostic interviews. Participants in the QTP trial met similar criteria using a different assessment tool. In all three trials, participants had to report using cannabis at least 5 days per week during the 28 days before joining the study. All participants were treated at the Substance Treatment and Research Service (STARS) of Columbia University/New York State Psychiatric Institute. Study enrollment for these trials occurred between March 2005 and February 2017.

The DRO study was a single-site, randomized, double-blind trial that compared dronabinol to a placebo. One hundred fifty-six participants were randomly assigned to receive either dronabinol or placebo for up to 8 weeks. The LFD study was also a single-site, randomized, double-blind trial that compared a combination of dronabinol and lofexidine to a placebo. One hundred twenty-two participants were randomly assigned to receive either active medication or placebo for up to 8 weeks. In both the DRO and LFD trials, participants also received weekly motivational enhancement and cognitive behavioral therapy. The QTP study was a single-site, randomized, double-blind trial comparing quetiapine to a placebo. One hundred thirty participants were randomly assigned to receive either active medication or placebo for up to 12 weeks. Participants in the QTP trial received weekly supportive behavioral treatment sessions aimed at promoting compliance with study medication and abstinence from marijuana.

Measures

To assess participants’ cannabis use, a modified Timeline Follow-Back (TLFB) assessment was used at twice-weekly visits. This method has been shown to be a reliable way to measure cannabis use, supported by its strong connection with urine drug screens in an earlier study. For the LFD study, participants’ quality of life was also measured at the start and end of the study using a specific questionnaire called the Quality of Life Enjoyment and Satisfaction Questionnaire-short form (QLES-Q-SF).

Statistical Analysis

Across all three studies, the number of days per week participants used cannabis often showed a "U-shaped" distribution, meaning more participants reported using 0 days or 7 days a week, with fewer reporting days in between. Because of this, weekly cannabis use was divided into three meaningful categories: heavy use (5–7 days per week), moderate use (2–4 days per week), and light use (0–1 day per week). Rules were applied to handle any missing data. If participants dropped out, weeks after their last study visit were considered missing. Statistical models were used to compare the chances of being in the light or moderate use category, relative to heavy use, for treatment groups versus placebo over time. These models also accounted for factors like age, sex, and baseline cannabis use, and for the QTP study, whether participants had co-occurring mood or anxiety disorders. Additional analyses were performed to ensure the main findings were not significantly affected by these factors or by participants dropping out of the study.

Results

Summary Results

Figure 1 shows the proportions of participants in heavy, moderate, and light use categories each week for both treatment and placebo groups. Across the three studies, there was no significant overall difference in the long-term pattern of cannabis use between the treatment groups and the placebo groups when adjusting for other factors. However, all three studies showed a similar trend: treatment groups were increasingly more likely to move from heavy use to moderate use compared to the placebo group. This consistent pattern was not observed for the shift from heavy use to light use.

Specifically, in the 12-week QTP study, the effect of quetiapine on moderate versus heavy use was not significantly different from placebo during the first four weeks. However, starting from week 5, the quetiapine group was significantly more likely to be in the moderate use category compared to the heavy use category (with a 56% higher chance at week 5, and a 230% higher chance by week 12). In the 8-week DRO study, dronabinol was significantly associated with higher odds of moderate use compared to heavy use starting from week 3, with the chance increasing to 117% higher by week 8. Similarly, in the 8-week LFD study, the lofexidine and dronabinol group was significantly associated with higher odds of moderate use compared to placebo during weeks 5–8, with the chance increasing to 179% higher by week 8.

There was no consistent pattern of association between treatments and light use compared to heavy use across these three analyses. In the QTP study, the quetiapine group was significantly less likely to be in the light use category compared to heavy use during weeks 1–5 only. In contrast, in the LFD study, the LFD group was significantly more likely to be in the light use category later in the study, during weeks 4–7. No significant treatment effect on light versus heavy use was observed in the DRO study. Sensitivity analyses, which involved removing covariates or treating participants who dropped out as heavy users, did not significantly change the original findings.

Proportion of Use Categories and Quality of Life

For the LFD study, the only one that assessed quality of life, a link was found between the proportion of heavy use weeks and quality of life scores at week 12. For every 10% decrease in the proportion of heavy use weeks, the quality of life score increased by an average of 0.87 points. This suggests that reducing heavy cannabis use was associated with an improved quality of life.

Discussion

Earlier analyses of two published trials did not find that complete abstinence or an overall reduction in days of use was greater among those on active treatment compared to the placebo. However, by conducting new analyses using an approach from a recently completed trial (comparing quetiapine to placebo), a similar pattern of results was found. Specifically, for all three studies, starting at the midpoint of each trial, the odds of moderate compared to heavy use were significantly higher in the treatment group. This pattern was not consistently seen for light use compared to heavy use across the treatment groups.

The reason for this observation is important. While most patients initially report that abstinence is their goal when they begin treatment, this often changes over time. Clinical observations suggest that the goal of abstinence is not always firmly held, especially if a participant is satisfied with a lower level of use. For the QTP trial, when participants were asked to rate what they considered "treatment success," the majority considered some reduction in use to be a success, rather than only complete abstinence. Achieving full abstinence, or even light use (1 day/week or less), may be difficult for individuals unless more powerful and safe medication interventions are developed.

Notably, when previous trials looked at reduction in overall days or amounts of use, they found no significant impact. However, when use was categorized into light, moderate, and heavy groups, there were signs of differences between treatment groups. There are several possible reasons for this difference. It might be harder for participants to accurately report the exact amount of cannabis used compared to simply stating whether they used on a given day. Also, because cannabis use days across these studies often showed a bimodal pattern (many users at 0 days or 7 days, fewer in between), using averages may not be as meaningful. Categorizing users might provide a better understanding of how cannabis use changes.

A key clinical question is whether changing from a heavy to a moderate use pattern is meaningful enough as a treatment outcome. Unlike alcohol, where reducing heavy drinking clearly leads to improved social functioning and reduced health issues, the benefits of reducing cannabis use for psychosocial function or psychiatric symptoms are less clear. However, findings from our re-analysis of the LFD trial suggest that reducing heavy cannabis use was associated with an improved quality of life.

While this paper presents a secondary analysis and relies on self-reported data, it supports the idea that further research into alternative outcome measures is important for cannabis treatment trials. In the current environment, abstinence as a sole outcome for CUD may not be a consistent goal for patients, nor is it necessarily the only outcome linked to clinical or functional improvement. Medication trials previously considered "negative" because they failed to achieve abstinence may warrant further analysis regarding their effectiveness in reducing cannabis use. It is notable that laboratory findings that appeared promising translated into positive results in outpatient settings when a categorical reduction in frequency of use was applied. For early-stage clinical trials, abstinence might be too high a hurdle, and reduction in use may be a more appropriate primary outcome measure.

Conclusion

In summary, this secondary analysis explores an alternative way of examining treatment outcomes for Cannabis Use Disorder. In the current environment, abstinence as the sole outcome for CUD is not always the patient's consistent goal, nor is it necessarily the only outcome connected to clinical or functional improvement. Medication trials previously judged as "negative" because they did not achieve abstinence may deserve further analysis regarding their effectiveness in reducing cannabis use. Future research is needed to determine the full clinical importance of the outcome measure used in this paper, as well as other reduction-in-use outcomes and their links to clinical and functional improvements.

Introduction

Many people do not see cannabis use disorder (CUD) as a serious issue, but it is a major public health problem. Many people in the United States use cannabis, and a large number of those seeking help for substance use problems are dealing with CUD. While talking therapies have been studied a lot to treat CUD, they do not work for everyone and are not always easy to get.

Many different medicines have been tested to treat CUD. Often, these studies happen in labs. Medicines are seen as hopeful in labs if they help people feel less high, reduce withdrawal symptoms, or use less cannabis after a break. However, good results in the lab often do not happen in real-world treatment studies. This might be because most studies focus on people stopping cannabis use completely. While some people want to stop completely, many who seek help prefer to just use less.

One large study with teenagers found that a medicine called n-acetylcysteine helped them stop using cannabis more than a dummy pill. But for adults, this medicine did not work better than a dummy pill to help them stop completely. This brings up the question of whether stopping completely is the only goal for treatment. For example, studies on alcohol often look at people reducing their drinking days or avoiding heavy drinking, because even using less can lead to a better life and fewer health problems.

Recently, three important studies looked at goals other than stopping completely. One study found that a medicine helped people have fewer cannabis withdrawal symptoms and use less cannabis. Two other studies also found that certain medicines helped people use cannabis less often or have lower levels of cannabis in their bodies.

A recent review of cannabis treatment studies found that most still aim for people to stop completely. But maybe it is time to rethink this. Our own group did two studies (DRO and LFD) where the main goal was for people to stop using cannabis. These studies did not show that the medicines worked better than a dummy pill for stopping completely. However, a newer study (QTP) looked at whether people reduced the number of days they used cannabis each week, rather than stopping completely. This approach showed promise, and we wanted to see if our older studies also showed similar benefits when looked at this new way.

Methods

Sample and Study Design

Information about how people were found for the studies, what checks they had, and who could join has been shared before. All people in the studies were looking for help with cannabis use as outpatients. They all met the rules for having cannabis dependence. For the DRO and LFD studies, people had to say they used cannabis at least 5 days a week in the month before joining. In the QTP study, people had to say they used cannabis on average 5 or more days a week in the month before joining. All studies took place at a special treatment center at Columbia University/New York State Psychiatric Institute. The DRO study was from 2005 to 2009, the LFD study from 2009 to 2014, and the QTP study from 2012 to 2017.

The DRO study was a blind study where some people got dronabinol and others got a dummy pill. Out of 184 people who joined, 156 were chosen by chance to get either dronabinol or the dummy pill for up to 8 weeks. The LFD study was also a blind study, comparing a dummy pill to dronabinol plus lofexidine. Out of 156 people, 122 were chosen by chance to get either the active medicines or the dummy pill for up to 8 weeks. In both these studies, all people also received weekly talking therapy.

The QTP study was a blind study comparing a dummy pill to quetiapine. Out of 130 people, 130 were chosen by chance to get either quetiapine or the dummy pill for up to 12 weeks. People in the QTP study also received weekly supportive counseling sessions with a research doctor. These sessions aimed to help them take their medicine and stop using cannabis.

Measures

To find out how much cannabis people used, a special interview called the timeline follow-back (TLFB) was used twice a week. This method has been shown to be good for tracking cannabis use. In the LFD study, people's quality of life was also checked at the start and end of the study using a special questionnaire.

Statistical Analysis

In all three studies, the number of days people used cannabis per week often fell into two main groups: either 0 days or 7 days, with fewer people in between. Because of this, cannabis use days per week were put into three groups that made sense clinically: heavy use (5–7 days a week), moderate use (2–4 days a week), and light use (0–1 day a week). If people missed some information about their cannabis use, rules were used to fill in the missing data. If people left the study early, the weeks after they left were counted as missing.

To look at the results, special math models were used. These models helped compare the chances of being in the light use or moderate use groups compared to the heavy use group, for those taking medicine versus those taking the dummy pill. The models also considered other things like age, gender, and how much cannabis people used at the start. For the QTP study, if someone also had mood or anxiety problems was also considered. Some extra checks were done to see if the results changed if people who left the study early were counted as heavy users, or if fewer other factors were considered.

Results

Summary Results

The pictures (Figure 1 in the original document) showed how many people were in the heavy, moderate, and light use groups each week, for both the medicine and dummy pill groups. Across all three studies, there was no major overall difference in the pattern of use over time between the groups taking medicine and those taking the dummy pill. However, all three studies showed similar patterns: people taking the medicine were more likely to move from heavy use to moderate use than those taking the dummy pill. This was not consistently seen for moving from heavy use to light use.

Details of Use Patterns

In all three studies, similar patterns were seen for people moving from heavy use to moderate use. In the groups taking medicine, the chances of being a moderate user instead of a heavy user were much higher than in the dummy pill groups. This started around the middle of each study. Specifically, in the 12-week QTP study, this difference began around week 5 and grew stronger. By week 12, people on quetiapine were about 3.3 times more likely to be moderate users than heavy users, compared to those on the dummy pill. In the 8-week DRO study, this difference started at week 3. By week 8, people on dronabinol were about 2.2 times more likely to be moderate users than heavy users, compared to the dummy pill group. In the 8-week LFD study, this pattern began during weeks 5 to 8. By week 8, people on lofexidine and dronabinol were about 2.8 times more likely to be moderate users than heavy users, compared to the dummy pill group.

There was no clear, repeated pattern for people moving from heavy use to light use across the three studies. In the QTP study, light use was actually less likely for those on quetiapine during the first few weeks. But in the LFD study, light use was more likely in the LFD group later in the study. No clear effect on light use was seen in the DRO study.

Checks were done to see if people leaving the study early or other factors changed the main results. These checks showed that the main findings about moderate use were still true.

Quality of Life

In the LFD study, the only one where quality of life was measured, there was a link between how much heavy use a person had and their quality of life score at the end of the study. For every 10% drop in heavy use weeks, quality of life scores went up a little.

Discussion

Earlier analyses of two studies did not find that people who took active medicine stopped using cannabis or used less overall more than those who took a dummy pill. However, when we looked at these studies again using a new method, similar to a recent study, we found something new. For all three studies, people on the active medicine were more likely to move from heavy cannabis use to moderate use, especially from the middle of the study onwards. This pattern was not consistently seen for moving to light use.

A key question is why this happened. Most people say they want to stop using cannabis completely when they start treatment, but this often changes over time. Many people are happy just using less. It might be very hard for people to stop completely without very strong (and safe) medicines. Also, it might be even harder to reach very light use (like 1 day a week) than moderate use (2-4 days a week) without stronger medicines.

It is worth noting that in two of our studies, we looked at how much people reduced their overall use or how much money they spent on cannabis, and we did not find big differences. But when we put people into heavy, moderate, or light use groups, we saw differences. This might be because it is harder for people to say exactly how much cannabis they used. Also, since many people either used cannabis every day or not at all, just using averages might not show the full picture. Grouping people helps us understand changes better.

A very important question for doctors is whether changing from heavy use to moderate use is truly helpful. For alcohol, reducing heavy drinking is known to improve a person's life and health. For cannabis, it is not as clear if using less helps with mental health problems or daily life issues. Our study on LFD did show that less heavy use was linked to a better quality of life. This suggests that reducing heavy use could be a meaningful goal for treatment. Medicines that looked promising in lab tests often did not work in real-world studies when the goal was stopping completely. But when we looked at reducing use in these studies, the lab findings seem to match up better with the real-world results. This means that for new drug studies, reducing use might be a more fitting main goal than full stopping.

A limit of this study is that people reported their own cannabis use. Even so, this study, along with other reviews, suggests that we should keep looking for different ways to measure how well cannabis treatments work for cannabis use disorder.

Conclusion

To sum up, this new look at old studies explores a different way to measure how well treatments for cannabis use disorder work. In today's world, stopping cannabis use completely is not always what patients want, nor is it the only way to show that treatment is helping someone's life improve. Medicine studies that were once thought to have failed because they did not lead to complete stopping might need another look to see if they helped people reduce their cannabis use. More research is needed to understand how important this idea of reducing use is for people's lives and health.