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.

Biomarkers, subgroup evaluation, and clinical trial design

BONETTI, MARCO
2012

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.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11565/3773322
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