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J Stat Plan Inference. 2008 Feb 1;138(2):308-320.

Development and Validation of Biomarker Classifiers for Treatment Selection.

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  • 1Richard Simon, D.Sc., Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda MD 20892-7434, U.S.A. 301.496-0975 (tel), 301.402-0560 (fax),


Many syndromes traditionally viewed as individual diseases are heterogeneous in molecular pathogenesis and treatment responsiveness. This often leads to the conduct of large clinical trials to identify small average treatment benefits for heterogeneous groups of patients. Drugs that demonstrate effectiveness in such trials may subsequently be used broadly, resulting in ineffective treatment of many patients. New genomic and proteomic technologies provide powerful tools for the selection of patients likely to benefit from a therapeutic without unacceptable adverse events. In spite of the large literature on developing predictive biomarkers, there is considerable confusion about the development and validation of biomarker based diagnostic classifiers for treatment selection. In this paper we attempt to clarify some of these issues and to provide guidance on the design of clinical trials for evaluating the clinical utility and robustness of pharmacogenomic classifiers.

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