| Autor: |
Charles eGreen, Joy eSchmitz, Jan eLindsay, Claudia ePedroza, Scott D. Lane, Rob eAgnelli, Kimberly eKjome, F Gerard Moeller |
| Jazyk: |
angličtina |
| Rok vydání: |
2012 |
| Předmět: |
|
| Zdroj: |
Frontiers in Psychiatry, Vol 3 (2012) |
| Druh dokumentu: |
article |
| ISSN: |
1664-0640 |
| DOI: |
10.3389/fpsyt.2012.00092 |
| Popis: |
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 samples for the historical dataset (Study 1: N = 64 complete observations) and current dataset (Study 2: N = 113 complete observations). 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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