4.1 Article

Clinical Trial Designs for Predictive Biomarker Validation: One Size Does Not Fit All

期刊

JOURNAL OF BIOPHARMACEUTICAL STATISTICS
卷 19, 期 3, 页码 530-542

出版社

TAYLOR & FRANCIS INC
DOI: 10.1080/10543400902802458

关键词

Biomarker; Enrichments designs; Predictive marker designs; Unselected designs

资金

  1. NATIONAL CANCER INSTITUTE [P30CA015083, U10CA025224] Funding Source: NIH RePORTER
  2. NCI NIH HHS [P30 CA015083, N01 CA015083, P30 CA015083-36, U10 CA025224-32, U10 CA025224, CA-25224, CA-15083] Funding Source: Medline

向作者/读者索取更多资源

Traditionally, anatomic staging systems have been used to provide predictions of individual patient outcome and, to a lesser extent, guide the choice of treatment in cancer patients. With targeted therapies, biomarkers have the potential for providing added value through an integrated approach to prediction using the genetic makeup of the tumor and the genotype of the patient for treatment selection and patient management. Specifically, biomarkers can aid in patient stratification (risk assessment), treatment response identification (surrogate markers), or differential diagnosis (identifying individuals who are likely to respond to specific drugs). In this study, we explore two major topics in relation to the design of clinical trials for predictive marker validation. First, we discuss the appropriateness of an enrichment (i.e., targeted) vs. an unselected design through case studies focusing on the clinical question(s) at hand, the strength of the preliminary evidence, and assay reproducibility. Second, we evaluate the efficiency (total number of events and sample size) of two unselected predictive marker designs for validation of a marker under a wide range of clinically relevant scenarios, exploring the impact of the prevalence of the marker and the hazard ratios for the treatment comparisons. The review and evaluation of these designs represents an essential step toward the goal of personalized medicine because we explicitly seek to explore and evaluate the methodology for the clinical validation of biomarker guided therapy.

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