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.

Abstract

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. 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. 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. 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.