Efficiency Enhancement in Testing Treatment Efficacy Across Multiple Populations Using Treatment Crossover Data

Stat Med. 2026 Jul;45(15-17):e70651. doi: 10.1002/sim.70651.

ABSTRACT

Recent advances in biotechnology and personalized medicine have driven the development of efficient clinical trial methodologies for assessing treatment efficacy across multiple populations defined by treatment effect modifiers. Within-patient comparison of different treatments is a promising approach for improving study efficiency across multiple populations by eliminating between-patient variability in treatment evaluation. This study provides a framework for evaluating treatment efficacy in multiple populations for $2\times 2$ crossover trials and evaluates the efficacy gain in comparison with the standard parallel-group analysis. Simulation experiments confirm that the crossover analysis consistently outperforms the parallel-group analysis in statistical power, especially when carryover effects are small. An application to a clinical trial in Type 2 diabetes demonstrates the efficiency advantages of the crossover analysis. These numerical results emphasize the potential of the crossover analysis for enhancing the efficiency of clinical development of personalized medicine.

PMID:42455565 | DOI:10.1002/sim.70651