Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, MSC7434, Bethesda, MD 20892-7434, U.S.A.
Stat Med. 2012 Nov 10;31(25):3031-40. doi: 10.1002/sim.5401. Epub 2012 Jun 19.
Developments in biotechnology and genomics are providing a biological basis for the heterogeneity of clinical course and response to treatment that have long been apparent to clinicians. The ability to molecularly characterize human diseases presents new opportunities to develop more effective treatments and new challenges for the design and analysis of clinical trials. In oncology, treatment of broad populations with regimens that benefit a minority of patients is less economically sustainable with expensive molecularly targeted therapeutics. The established molecular heterogeneity of human diseases requires the development of new paradigms for the design and analysis of randomized clinical trials as a reliable basis for predictive medicine. We review prospective designs for the development of new therapeutics and predictive biomarkers to inform their use. We cover designs for a wide range of settings. At one extreme is the development of a new drug with a single candidate biomarker and strong biological evidence that marker negative patients are unlikely to benefit from the new drug. At the other extreme are Phase III clinical trials involving both genome-wide discovery of a predictive classifier and internal validation of that classifier. We have outlined a prediction-based approach to the analysis of randomized clinical trials that both preserves the Type I error and provides a reliable internally validated basis for predicting which patients are most likely or unlikely to benefit from the new regimen.
生物技术和基因组学的发展为临床病程和治疗反应的异质性提供了生物学基础，而这些异质性长期以来一直为临床医生所注意。能够对人类疾病进行分子特征分析，为开发更有效的治疗方法提供了新的机会，同时也为临床试验的设计和分析带来了新的挑战。在肿瘤学领域，用少数患者受益的方案治疗广泛的人群，对于昂贵的分子靶向治疗来说，在经济上不太可持续。人类疾病的既定分子异质性要求为随机临床试验的设计和分析开发新的范例，作为预测医学的可靠基础。我们回顾了开发新疗法和预测性生物标志物的前瞻性设计，以告知其使用。我们涵盖了广泛的设置。一种极端情况是开发一种具有单一候选生物标志物的新药，并且有强有力的生物学证据表明，标记阴性患者不太可能从新药中获益。另一种极端情况是涉及预测分类器的全基因组发现和对该分类器的内部验证的 III 期临床试验。我们已经概述了一种基于预测的随机临床试验分析方法，这种方法既保留了 I 型错误，又为预测哪些患者最有可能或不太可能从新方案中获益提供了可靠的内部验证基础。
