The Influence of Baseline Marijuana Use on Treatment of Cocaine Dependence: Application of an Informative-Priors Bayesian Approach

Abstract

Background: Marijuana use is prevalent among patients with cocaine dependence and often non-exclusionary in clinical trials of potential cocaine medications. The dual-focus of this study was to (1) examine the moderating effect of baseline marijuana use on response to treatment with levodopa/carbidopa for cocaine dependence; and (2) apply an informative-priors, Bayesian approach for estimating the probability of a subgroup-by-treatment interaction effect. Method: A secondary data analysis of two previously published, double-blind, randomized controlled trials provided complete data for the historical (Study 1: N = 64 placebo), and current (Study 2: N = 113) data sets. Negative binomial regression evaluated Treatment Effectiveness Scores (TES) as a function of medication condition (levodopa/carbidopa, placebo), baseline marijuana use (days in past 30), and their interaction. Results: Bayesian analysis indicated that there was a 96% chance that baseline marijuana use predicts differential response to treatment with levodopa/carbidopa. Simple effects indicated that among participants receiving levodopa/carbidopa the probability that baseline marijuana confers harm in terms of reducing TES was 0.981; whereas the probability that marijuana confers harm within the placebo condition was 0.163. For every additional day of marijuana use reported at baseline, participants in the levodopa/carbidopa condition demonstrated a 5.4% decrease in TES; while participants in the placebo condition demonstrated a 4.9% increase in TES. Conclusion: The potential moderating effect of marijuana on cocaine treatment response should be considered in future trial designs. Applying Bayesian subgroup analysis proved informative in characterizing this patient-treatment interaction effect.

Clinical neuropharmacology of cocaine reinforcement: A narrative review of human laboratory self‐administration studies

“…Although these methods have many benefits, they often heavily rely on p ‐values, which are typically misinterpreted and do not provide information about the magnitude of a treatment effect, which is important when determining potential clinical efficacy of a drug (Wijeysundera et al, 2009). Alternative statistical methods, such as Bayesian statistical inference, may provide additional benefits to analysis of self‐administration studies, such as directly addressing the alternative hypothesis, rather than indirectly rejecting the null hypothesis (Green et al, 2012). Bayesian statistical inference has been effectively used in clinical trials (see Green et al, 2012; Wijeysundera et al, 2009) and have been recommended to be used in conjunction with typical inferential statistical methods.…”

“…Alternative statistical methods, such as Bayesian statistical inference, may provide additional benefits to analysis of self‐administration studies, such as directly addressing the alternative hypothesis, rather than indirectly rejecting the null hypothesis (Green et al, 2012). Bayesian statistical inference has been effectively used in clinical trials (see Green et al, 2012; Wijeysundera et al, 2009) and have been recommended to be used in conjunction with typical inferential statistical methods. Future cocaine self‐administration research may benefit from the use of Bayesian statistical inference in addition to other common analyses in self‐administration research, as these methods can detect subtle differences in effects with smaller sample sizes (Lee & Song, 2004).…”

Impact of Cannabis Use on Treatment Outcomes among Adults Receiving Cognitive-Behavioral Treatment for PTSD and Substance Use Disorders

“…However, other studies suggest that cannabis use either before entering or after being discharged from treatment may be associated with adverse treatment outcomes among opioid and cocaine-dependent patients [ 38 , 39 , 40 ]. For example, a prospective study of heroin-abstinent patients found that cannabis use was a significant predictor of heroin use resumption [ 40 ].…”

“…For example, a prospective study of heroin-abstinent patients found that cannabis use was a significant predictor of heroin use resumption [ 40 ]. A secondary analysis of two completed clinical trials of treatment for cocaine dependence found an effect of baseline marijuana use on response to treatment for cocaine dependence; specifically, more days of marijuana use at baseline predicted lower treatment effectiveness (cocaine-negative urines) among those receiving levodopa/carbidopa, but not in the placebo condition [ 39 ]. The authors speculated that higher baseline marijuana use may be a proxy for cocaine severity.…”