Quantifying Treatment Benefit in Molecular Subgroups to Assess a Predictive Biomarker.

ABSTRACT: An increased interest has been expressed in finding predictive biomarkers that can guide treatment options for both mutation carriers and noncarriers. The statistical assessment of variation in treatment benefit (TB) according to the biomarker carrier status plays an important role in evaluating predictive biomarkers. For time-to-event endpoints, the hazard ratio (HR) for interaction between treatment and a biomarker from a proportional hazards regression model is commonly used as a measure of variation in TB. Although this can be easily obtained using available statistical software packages, the interpretation of HR is not straightforward. In this article, we propose different summary measures of variation in TB on the scale of survival probabilities for evaluating a predictive biomarker.

SUBMITTER: Iasonos A 

PROVIDER: S-EPMC4856220 | biostudies-literature | 2016 May

REPOSITORIES: biostudies-literature