Clinical trials enroll subjects expected to benefit from the treatment under investigation, although the magnitude of their benefits, when it exits, may vary by their background characteristics. For a completed trial that demonstrates treatment efficacy in the overall population, subgroup analysis are usually carried out for checking consistency of treatment effect across subgroups for proper interpretation of study findings and for providing guidance on treatment use. However, observed heterogeneity in treatment effect across subgroups can be, partly at least, due to chance factors; furthermore, true heterogeneity, when present, may not be detected by statistical tests due to their low power. This tutorial considers these issues related to subgroup analyses for a completed trial and investigates whether subgroup findings can be supportive for those of the overall population. In addition, it discusses statistical considerations for the design and analysis of a confirmatory clinical trial with the objective of establishing efficacy claims in a targeted subgroup and the overall population.
At the conclusion of this tutorial, participants should be able to:
- Identify the impact of chance findings on the interpretation of subgroup analysis findings
- Describe how to critically assess findings of testing for treatment-by-subgroup interaction and their utility in determining the treatments use
- Discuss how to handle statistical considerations, including study power and multiplicity issues, for the design and analysis of a clinical trial with claim for a targeted subgroup