Subgroup analyses in addition to the total study population analysis are common in clinical trials. In this presentation we discuss some of the common pitfalls of subgroup analyses which limit their utility to provide confirmatory evidence for subgroup treatment effects. Then we introduce a flexible sequential testing strategy for testing for both the overall and a subgroup hypothesis which controls strongly the familywise Type I error rate. The testing strategy takes into account a pre-specified degree of consistency in the efficacy findings of the subgroup and the total population as well as the dependency between test statistics for the subgroup and the overall study population. We discuss the power performance of this new method and provide significance levels for subgroup analysis. Finally, we illustrate its application through retrospective analysis of clinical trial data.