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Updated: Feb 18, 2026

Selecting Multiple Biomarker Subsets with Similarly Effective Binary Classification Performances
Published on: October 11, 2018
Futility for subgroup analyses in the adaptive signature design
1GSK Vaccines, Rue de L'Institut 89, Rixensart, Belgium.
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.
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