Statistics in Oncology Clinical Trials
Adaptive randomized phase II design for biomarker threshold selection and independent evaluation
Abstract
Background: Frequently a biomarker capable of defining a patient population with enhanced response to an experimental agent is not fully validated with a known threshold at the start of a phase II trial. When such candidate predictive markers are evaluated and/or validated retrospectively, over-accrual of patients less likely to benefit from the regimen may result, leading to underpowered analyses or sub-optimal patient care.
Purpose: We propose an adaptive randomized phase II study design incorporating prospective biomarker threshold identification (or non-identification), possible early futility stopping, potential mid-trial accrual restriction to marker-positive subjects, and final marker and treatment evaluation in the patient population identified as most likely to benefit.
Methods: An interim analysis is used to determine whether an initially unselected trial should stop early for futility, continue without a promising marker, or adapt accrual and resize (up to a pre-determined maximum) according to a promising biomarker. Final efficacy analyses are performed in the target population identified at the interim as most likely to benefit from the experimental regimen. Simulation studies demonstrate control of false-positive error rates, power, reduced average sample size, and other favorable aspects.
Results: The design performs well at identifying a truly predictive biomarker at interim analysis, and subsequently restricting accrual to patients most likely to benefit from the experimental treatment. Type I and type II error rates are adequately controlled by restricting the range of marker prevalence via the candidate thresholds, and by careful consideration of the timing of interim analysis.
Conclusions: In situations where identification and validation of a naturally continuous biomarker are desired within a randomized phase II trial, the design presented herein offers a potential solution.
Purpose: We propose an adaptive randomized phase II study design incorporating prospective biomarker threshold identification (or non-identification), possible early futility stopping, potential mid-trial accrual restriction to marker-positive subjects, and final marker and treatment evaluation in the patient population identified as most likely to benefit.
Methods: An interim analysis is used to determine whether an initially unselected trial should stop early for futility, continue without a promising marker, or adapt accrual and resize (up to a pre-determined maximum) according to a promising biomarker. Final efficacy analyses are performed in the target population identified at the interim as most likely to benefit from the experimental regimen. Simulation studies demonstrate control of false-positive error rates, power, reduced average sample size, and other favorable aspects.
Results: The design performs well at identifying a truly predictive biomarker at interim analysis, and subsequently restricting accrual to patients most likely to benefit from the experimental treatment. Type I and type II error rates are adequately controlled by restricting the range of marker prevalence via the candidate thresholds, and by careful consideration of the timing of interim analysis.
Conclusions: In situations where identification and validation of a naturally continuous biomarker are desired within a randomized phase II trial, the design presented herein offers a potential solution.
