Simon Richard
Richard 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),
J Stat Plan Inference. 2008 Feb 1;138(2):308-320. doi: 10.1016/j.jspi.2007.06.010.
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.
许多传统上被视为单一疾病的综合征在分子发病机制和治疗反应性方面具有异质性。这常常导致开展大型临床试验,以确定异质性患者群体的微小平均治疗益处。在这类试验中显示出有效性的药物随后可能会被广泛使用,从而导致许多患者接受无效治疗。新的基因组学和蛋白质组学技术为选择可能从治疗中获益且无不可接受不良事件的患者提供了强大工具。尽管有大量关于开发预测性生物标志物的文献,但对于基于生物标志物的诊断分类器用于治疗选择的开发和验证仍存在相当大的困惑。在本文中,我们试图阐明其中的一些问题,并为评估药物基因组学分类器的临床效用和稳健性的临床试验设计提供指导。