A Meta-Regression of Trial Features Predicting the Effects of Alcohol Use Disorder Pharmacotherapies on Drinking Outcomes in Randomized Clinical Trials: A Secondary Data Analysis. (1st March 2022) - Grodin, Erica N; Donato, Suzanna; Du, Han; Green, ReJoyce; Bujarski, Spencer; Ray, Lara A
Abstract: Aims: To test whether two critical design features, inclusion criteria of required pre-trial abstinence and pre-trial alcohol use disorder (AUD) diagnosis, predict the likelihood of detecting treatment effects in AUD pharmacotherapy trials. Methods: This secondary data analysis used data collected from a literature review to identify randomized controlled pharmacotherapy trials for AUD. Treatment outcomes were selected into abstinence and no heavy drinking. Target effect sizes were calculated for each outcome and a meta-regression was conducted to test the effects of required pre-trial abstinence, required pre-trial AUD diagnosis, and their interaction on effect sizes. A sub-analysis was conducted on trials, which included FDA-approved medications for AUD. Results: In total, 118 studies testing 19 medications representing 21, 032 treated participants were included in the meta-regression analysis. There was no significant effect of either predictor on abstinence or no heavy drinking outcomes in the full analysis or in the sub-study of FDA-approved medications. Conclusion: By examining these design features in a quantitative, rather than qualitative, fashion the present study advances the literature and shows that requiring AUD diagnosis or requiring pre-trial abstinence do not impact the likelihood of a significant medication effect in the trial. Abstract : Short Summary: A secondary meta-regression of 118 randomized controlled trials of alcohol use disorder pharmacotherapies was conducted to test if design features predict the likelihood of detecting treatment effects. There was no significant effect of either pre-trial abstinence or pre-trial AUD diagnosis requirements on abstinence or heavy drinking outcomes.