Duke Cancer Institute, Duke Cancer Care Research Program, Durham, NC, USA.
Cancer J. 2011 Jul-Aug;17(4):235-8. doi: 10.1097/PPO.0b013e31822c3944.
Comparative effectiveness research (CER) is meant to provide evidence about the relative risks and benefits of different treatment options. It is gaining visibility as a tool to address the evidence gaps that clinicians struggle with every day; however, CER is particularly challenging in oncology as there is great variability in how individuals respond to interventions, and a wide range of drugs and procedures are available. In order to overcome these obstacles and conduct reliable CER studies, it is critical to create a robust data infrastructure to support it.The Center for Medical Technology Policy held its first annual CER Summit in November 2010, with a particular focus on oncology. A number of critical informatics themes emerged including the need for consistent data standards, registry reform, tools to assist trial accrual, and data to integrate into value deliberations. Addressing the data issues highlighted in this report will provide a significant opportunity to improve the health of our medical system.
比较疗效研究（CER）旨在提供关于不同治疗选择的相对风险和益处的证据。它作为一种工具越来越受到关注，可用于解决临床医生每天面临的证据缺口问题；然而，由于个体对干预措施的反应存在很大差异，并且有多种药物和程序可供选择，因此 CER 在肿瘤学领域尤其具有挑战性。为了克服这些障碍并进行可靠的 CER 研究，建立一个强大的数据基础设施来支持它至关重要。医学技术政策中心于 2010 年 11 月举办了第一届年度 CER 峰会，特别关注肿瘤学。出现了许多关键的信息学主题，包括需要一致的数据标准、登记册改革、辅助试验入组的工具以及纳入价值审议的数据。解决本报告中强调的数据问题将为改善我们的医疗系统健康状况提供一个重要机会。
