Statistical Considerations for Subgroup Analyses

作者：Xiaofei Wang, S. Piantadosi, J. Le-Rademacher, S. Mandrekar · 发表于：Journal of Thoracic Oncology · 年份：2020 · DOI：10.1016/j.jtho.2020.12.008 · 被引用次数：108 · 研究领域：Medicine

https://doi.org/10.1016/j.jtho.2020.12.008 Introduction Randomized clinical trials (RCTs) are conducted to evaluate the effect of an experimental treatment on outcomes of a target patient population. Eligibility criteria for large trials are often broad to ensure that the trial results can be generalized to a larger patient population. Subgroup analyses, either specified a priori or post hoc, are perfo rmed to evaluate the treatment effect specific to a subgroup of treated patients. Regardless of whether a subgroup analysis is specified a priori or post hoc, investigators must consider inflated false-positive rates, chance differences in observed treatment effects, low power for the comparisons of interest, and interpretation of the subgroup results. Subgroup analyses in clinical trials and observational studies have been discussed in regulatory agency guidelines, and comprehensive review of this topic has been published in applied statistical journals. This article reviews key statistical concepts associated with planning, conducting, and interpreting subgroup analyses in RCTs. It also highlights the pitfalls in conducting undisciplined subgroup analyses.