Comparing pharmacological treatments for cocaine dependence: Incorporation of methods for enhancing generalizability in meta-analytic studies.

OBJECTIVES: Few head-to-head comparisons of cocaine dependence medications exist, and combining data from different randomized controlled trials (RCTs) is fraught with methodological challenges including limited generalizability of the RCT findings. This study applied a novel meta-analytic approach to data of cocaine dependence medications. METHODS: Data from 4 placebo-controlled RCTs (Reserpine, Modafinil, Buspirone, and Ondansetron) were obtained from the National Institute of Drug Abuse Clinical Trials Network (n = 456). The RCT samples were weighted to resemble treatment-seeking patients (Treatment Episodes Data Set-Admissions) and individuals with cocaine dependence in general population (National Survey on Drug Use and Health). We synthesized the generalized outcomes with pairwise meta-analysis using individual-level data and compared the generalized outcomes across the 4 RCTs with network meta-analysis using study-level data. RESULTS: Weighting the data by the National Survey on Drug Use and Health generalizability weight made the overall population effect on retention significantly larger than the RCT sample effect. However, there was no significant difference between the population effect and the RCT sample effect on abstinence. Weighting changed the ranking of the effectiveness across treatments. CONCLUSIONS: Applying generalizability weights to meta-analytic studies is feasible and potentially provides a useful tool in assessing comparative effectiveness of treatments for substance use disorders in target populations.

Duke Scholars

Author Hwanhee Hong Biostatistics & Bioinformatics, Division of Biostatistics