Evidence of subgroup differences in meta‐analyses evaluating medications for alcohol use disorder: An umbrella review

Abstract

AbstractRandomized controlled trials (RCTs) evaluating medications for alcohol use disorder (AUD) often examine heterogeneity of treatment effects through subgroup analyses that contrast effect estimates in groups of patients across individual demographic, clinical, and study design‐related characteristics. However, these analyses are often not prespecified or adequately powered, highlighting the potential role of subgroup analyses in meta‐analysis. Here, we conducted an umbrella review (i.e., a systematic review of meta‐analyses) to determine the range and characteristics of reported subgroup analyses in meta‐analyses of AUD medications. We searched PubMed to identify meta‐analyses of RCTs evaluating medications for the management of AUD, alcohol abuse, or alcohol dependence in adults. We sought studies that measured drinking‐related outcomes; quality of life, function, and rates of mortality; adverse events; and dropout. We considered meta‐analyses that reported the results from formal subgroup analyses (comparing the summary effects across subgroup levels); summary effect estimates stratified across subgroup levels; and meta‐regression, regression, or correlation‐based subgroup analyses. We analyzed nine meta‐analyses that included 61 formal subgroup analyses (median = 6 per meta‐analysis), of which 33 (54%) were based on baseline participant‐level and 28 (46%) were based on trial‐level characteristics. Of the 58 subgroup analyses with either a p‐value from a subgroup test or a statement by the authors that the subgroup analyses were not statistically significant, eight (14%) were statistically significant at the p < 0.05 level. Twelve meta‐analyses reported the results of 102 meta‐regression analyses, of which 25 (25%) identified statistically significant predictors of the relevant outcome of interest; nine (9%) were based on baseline participant‐level and 93 (91%) were based on trial characteristics. Subgroup analyses across meta‐analyses of AUD medications often focus on study‐level characteristics, which may not be as clinically informative as subgroup analyses based on participant‐level characteristics. Opportunities exist for future meta‐analyses to standardize their subgroup methodology, focus on more clinically informative participant‐level characteristics, and use predictive approaches to account for multiple relevant variables.