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设计临床研究以识别癌症研究中预测性生物标志物的策略。

Strategies to design clinical studies to identify predictive biomarkers in cancer research.

机构信息

Department of Oncology, University Clinic of Navarra, Pamplona, Spain; Health Research Institute of Navarra (IDISNA), Pamplona, Spain.

Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA.

出版信息

Cancer Treat Rev. 2017 Feb;53:79-97. doi: 10.1016/j.ctrv.2016.12.005. Epub 2016 Dec 30.

DOI:10.1016/j.ctrv.2016.12.005
PMID:28088073
Abstract

The discovery of reliable biomarkers to predict efficacy and toxicity of anticancer drugs remains one of the key challenges in cancer research. Despite its relevance, no efficient study designs to identify promising candidate biomarkers have been established. This has led to the proliferation of a myriad of exploratory studies using dissimilar strategies, most of which fail to identify any promising targets and are seldom validated. The lack of a proper methodology also determines that many anti-cancer drugs are developed below their potential, due to failure to identify predictive biomarkers. While some drugs will be systematically administered to many patients who will not benefit from them, leading to unnecessary toxicities and costs, others will never reach registration due to our inability to identify the specific patient population in which they are active. Despite these drawbacks, a limited number of outstanding predictive biomarkers have been successfully identified and validated, and have changed the standard practice of oncology. In this manuscript, a multidisciplinary panel reviews how those key biomarkers were identified and, based on those experiences, proposes a methodological framework-the DESIGN guidelines-to standardize the clinical design of biomarker identification studies and to develop future research in this pivotal field.

摘要

发现可靠的生物标志物来预测抗癌药物的疗效和毒性仍然是癌症研究的关键挑战之一。尽管相关性很强,但尚未建立有效的研究设计来确定有前途的候选生物标志物。这导致了大量使用不同策略的探索性研究的激增,其中大多数未能确定任何有前途的靶点,很少得到验证。由于缺乏适当的方法学,许多抗癌药物的开发也低于其潜力,因为未能确定预测性生物标志物。一些药物将被系统地用于许多不会从中受益的患者,导致不必要的毒性和成本,而其他药物由于我们无法识别出它们在哪些特定患者群体中有效的情况下而无法注册。尽管存在这些缺陷,但已经成功识别和验证了少数杰出的预测性生物标志物,并改变了肿瘤学的标准实践。在本文中,一个多学科小组审查了这些关键生物标志物是如何被识别的,并基于这些经验,提出了一个方法学框架——DESIGN 指南——来规范生物标志物识别研究的临床设计,并在这一关键领域开展未来的研究。

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