Literature DB >> 35229869

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.

Erica N Grodin1, Suzanna Donato1, Han Du1, ReJoyce Green1, Spencer Bujarski1, Lara A Ray1,2.   

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.
© The Author(s) 2022. Medical Council on Alcohol and Oxford University Press. All rights reserved.

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Mesh:

Year:  2022        PMID: 35229869      PMCID: PMC9465523          DOI: 10.1093/alcalc/agac004

Source DB:  PubMed          Journal:  Alcohol Alcohol        ISSN: 0735-0414            Impact factor:   3.913


  33 in total

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