Biomarkers, subgroup evaluation, and clinical trial design

Stuart G. Baker, Barnett S. Kramer, Daniel J. Sargent, Marco Bonetti

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Advances in clinical and basic sciences are raising the potential to use genetic and clinical biomarkers to identify a subgroup of patients who would most likely benefit from treatment, and to evaluate the benefit of treatment in that subgroup. To make full use of this potential, special clinical trial designs and analyses are needed. For identifying and evaluating a subgroup based on a single continuous biomarker, the most informative approach is the biomarker-analysis design, which is a randomized trial whose analysis involves estimation of the treatment benefit within patient groups defined with respect to various cutpoints or intervals of the biomarker. For identifying and evaluating a subgroup considering a range of possible markers, the adaptive signature design is recommended. In the adaptive signature design, participants are randomly split into training and test samples, a rule for creating the subgroup is formulated in the training sample, and treatment benefit is estimated in the test sample. The adaptive signature design can be usefully extended via the sliding-window subgroup plot that was originally developed for the biomarker-analysis design.

Original languageEnglish (US)
Pages (from-to)187-192
Number of pages6
JournalDiscovery Medicine
Volume13
Issue number70
StatePublished - Mar 1 2012

ASJC Scopus subject areas

  • General Medicine

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