title: Predictive biomarkers in colorectal cancer: usage, validation, and design in clinical trials.
abstract: As cancer treatment development has shifted its attention to targeted therapies, it is becoming increasingly important to provide tools for selecting the right treatment for an individual patient to achieve optimal clinical benefit. Biomarkers, identified and studied in the process of understanding the nature of the disease at the molecular pathogenesis level, have been increasingly recognized as a critical aspect in more accurate diagnosis, prognosis assessment, and therapeutic targeting. Predictive biomarkers, which can aid treatment decisions, require extensive data for validation. In this article, we discuss the definition, clinical usages, and more extensively the clinical trial designs for the validation of predictive biomarkers. Predictive biomarker validation methods can be broadly grouped into retrospective and prospective designs. Retrospective validation utilizes data from previously conducted prospective randomized controlled trials. Prospective designs include enrichment designs, treatment-by-marker interaction designs, marker-based strategy designs, and adaptive designs. We discuss each design with examples and provide comparisons of the advantages and disadvantages among the different designs. We conclude that the combination of scientific, clinical, statistical, ethical, and practical considerations provides guidance for the choice of the clinical trial design for validation of each proposed predictive biomarker.
authors.affiliation: Department of Health Science Research, Mayo Clinic, Rochester, MN 55905, USA.
authors.forename: Qian
authors.initials: Q
authors.lastname: Shi
authors.forename: Sumithra J
authors.initials: SJ
authors.lastname: Mandrekar
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Sargent
mesh_terms: D014408:Biomarkers, Tumor / Q000032:analysis*; D002986:Clinical Trials as Topic; D015179:Colorectal Neoplasms / Q000378:metabolism* / Q000473:pathology* / Q000628:therapy*; D003657:Decision Making; D006801:Humans; D011237:Predictive Value of Tests; D012107:Research Design
chemical_list: D014408:Biomarkers, Tumor