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

随机临床试验中预测酒精使用障碍药物治疗对饮酒结果影响的试验特征的荟萃回归分析:一项二次数据分析

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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.

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