Futility for subgroup analyses in the adaptive signature design

Abstract

Subgroup analyses in clinical trials are becoming increasingly important. In cancer research, more and more targeted therapies are explored from which probably only a portion of the whole population will benefit. An adaptive design for subgroup selection with identification of a subgroup, the adaptive signature design, was proposed in the literature. Unfortunately, measuring and validating the variables defining the subgroup (i.e. biomarkers) can be extremely expensive. For this reason, we propose an extension of this design where subgroup analysis is not performed when the overall results suggest that it is unlikely to achieve statistical significance in the subgroup. Avoiding measuring and validating expensive biomarkers in this case can save resources that could be used on more promising research.

Adaptive Signature Design- review of the biomarker guided adaptive phase –III controlled design

“…Recent researches with ASD include extensions in the subgroup analysis arena where inclusion of futility or decision rule can contribute to the prevention of cost and complications of defining subgroups based on complex and expensive biomarkers, such as multivariate Quantitative polymerase chain reaction (qPCR). Frequentist and Bayesian approaches based on conditional power and predictive power respectively, with continuous efficacy endpoint restricts conduction of subgroup analysis, if the overall test confirms lack of statistical significance in the subgroup [ 52 ]. New techniques of subgroup selection based on utility function whose formulation includes the subgroup size and clinical indicator with the objective of maximizing power for treatment effect in the selected subgroup with baseline covariates such as age, gender, systolic blood pressure, heart rate, a simple risk index and binary endpoints is addressed.…”