title: Reader reaction on estimation of treatment effects in all-comers randomized clinical trials with a predictive marker.
abstract: For a fallback randomized clinical trial design with a marker, Choai and Matsui (2015, Biometrics 71, 25-32) estimate the bias of the estimator of the treatment effect in the marker-positive subgroup conditional on the treatment effect not being statistically significant in the overall population. This is used to construct and examine conditionally bias-corrected estimators of the treatment effect for the marker-positive subgroup. We argue that it may not be appropriate to correct for conditional bias in this setting. Instead, we consider the unconditional bias of estimators of the treatment effect for marker-positive patients.
authors: Biometric Research Program, National Cancer Institute, Bethesda, Maryland 20852, U.S.A.
authors: Edward L
authors: EL
authors: Korn
authors: Biometric Research Program, National Cancer Institute, Bethesda, Maryland 20852, U.S.A.
authors: Boris
authors: B
authors: Freidlin
mesh_terms: D015982:Bias; D015415:Biomarkers / Q000032:analysis*; D002986:Clinical Trials as Topic; D006801:Humans
chemical_list: D015415:Biomarkers
keywords: Adaptive signature design; Conditional bias; Fallback approach; Predictive markers; Randomized clinical trials