Interpretation of results from subset analyses within overviews of randomized clinical trials

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Abstract
Evaluating treatment effects within different subsets of patients is a common practice in the analysis of individual randomized clinical trials. Such analyses are limited, however, by the number of patients available. Overviews, by providing evidence based on large numbers of patients, can be useful for overcoming the difficulties of detecting therapeutic effects within subsets of patients. However, inconsistent subset definitions, misclassification of patients, and incomplete availability of patient subsets from the trials included in the overview bias the estimates of effect size.Separate analyses ofsubsets of studiesare also possible within an overview. Studies being pooled generally differ with respect to treatments applied, control groups, patient eligibility, quality control, study conduct, and follow‐up maturity. Separate comparisons within subsets defined by these features will be misinterpreted unless confounding factors are recognized. Indirect comparisons between overviews have the same informative value as nonrandomized trials with historical controls.