title: 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.
  
  
  OBJECTIVE
  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.
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA. Renfro.lindsay@mayo.edu.
authors.forename: Lindsay A
authors.initials: LA
authors.lastname: Renfro
authors.affiliation: Novartis Oncology, East Hanover, NJ 07936, USA.
authors.forename: Christina M
authors.initials: CM
authors.lastname: Coughlin
authors.affiliation: Department of Oncology, Mayo Clinic, Rochester, MN, USA.
authors.forename: Axel M
authors.initials: AM
authors.lastname: Grothey
authors.affiliation: Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Sargent
keywords: Adaptive design; interim futility analysis; phase II trial; predictive biomarker; randomized clinical trial; threshold identification