Pharm Stat. 2025 Sep-Oct;24(5):e70027. doi: 10.1002/pst.70027.
ABSTRACT
A major emphasis in personalized medicine is to optimally treat subgroups of patients who may benefit from certain therapeutic agents. One relevant study design is the targeted design, in which patients have consented for their specimens to be obtained at baseline and the specimens are sent to a laboratory for assessing the biomarker status prior to randomization. Here, only biomarker-positive patients will be randomized to either an experimental or the standard of care arms. Many biomarkers, however, are derived from patient tissue specimens, which are heterogeneous leading to variability in the biomarker levels and status. This heterogeneity would have an adverse impact on the power of an enriched biomarker clinical trial. In this article, we show the adverse effect of using the uncorrected sample size and overcome this challenge by presenting an approach to adjust for misclassification for the targeted design. Specifically, we propose a sample size formula that adjusts for misclassification and apply it in the design of two phase III clinical trials in renal and prostate cancer.
PMID:40711765 | DOI:10.1002/pst.70027
