A Bayesian approach to the interpretation of subgroup results in clinical trials.

Problems of interpretation often arise when patients who have been entered into a randomized clinical trial are post-stratified according to prognostic descriptors, and treatment comparisons performed within subgroups. In this paper a Bayesian approach to interpreting these comparisons is proposed, which takes into account the investigator's prior expectations concerning the relative magnitudes of treatment effects in different subgroups.