Originally published as JCO Early Release 10.1200/JCO.2009.22.3701 on July 13 2009

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Clinical Trial Designs for Predictive Biomarker Validation: Theoretical Considerations and Practical Challenges

From the Department of Health Sciences Research, Mayo Clinic, Rochester, MN.

Corresponding author: Sumithra J. Mandrekar, PhD, Department of Health Sciences Research, Mayo Clinic, 200 1st ST SW, Rochester, MN 55905; e-mail: mandrekar.sumithra{at}mayo.edu.

Purpose Biomarkers can add substantial value to current medical practice by providing an integrated approach to prediction using the genetic makeup of the tumor and the genotype of the patient to guide patient-specific treatment selection. We discuss and evaluate various clinical trial designs for the validation of biomarker-guided therapy.

Methods Designs for predictive marker validation are broadly classified as retrospective (ie, using data from previously well-conducted randomized controlled trials [RCTs]) versus prospective (enrichment, unselected, hybrid, or adaptive analysis). We discuss the salient features of each design in the context of real trials.

Results Well-designed retrospective analysis from well-conducted prospective RCTs can bring forward effective treatments to marker-defined subgroups of patients in a timely manner (eg, KRAS and colorectal cancer). Enrichment designs are appropriate when preliminary evidence suggest that patients with or without that marker profile do not benefit from the treatments in question; however, this may sometimes leave questions unanswered (eg, trastuzumab and breast cancer). An unselected design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (eg, epidermal growth factor receptor and lung cancer). Hybrid designs are appropriate when preliminary evidence demonstrate the efficacy of certain treatments for a marker-defined subgroup, making it unethical to randomly assign patients with that marker status to other treatments (eg, multigene assay and breast cancer). Adaptive analysis designs allow for prespecified marker-defined subgroup analyses of data from an RCT.

Conclusion The implementation of these design strategies will lead to a more rapid clinical validation of biomarker-guided therapy.

Presented in part at the 2008 American Society of Clinical Oncology/National Cancer Institute/European Organisation for Research and Treatment of Cancer Annual Meeting on Molecular Markers in Cancer, October 30-November 1, 2008, Hollywood, FL.

Supported in part by National Cancer Institute Grants No. CA-15083 (Mayo Clinic Cancer Center) and CA-25224 (North Central Cancer Treatment Group).

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

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