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Front Psychiatry. 2012 Oct 30;3:92. doi: 10.3389/fpsyt.2012.00092. eCollection 2012.

The influence of baseline marijuana use on treatment of cocaine dependence: application of an informative-priors bayesian approach.

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  • 1University of Texas Health Sciences Center at Houston Houston, TX, USA.

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.

KEYWORDS:

Bayesian; cocaine; marijuana; subgroup analysis; treatment response

PMID:
23115553
[PubMed]
PMCID:
PMC3483568
Free PMC Article
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