The Increasing Importance of Rigorous Real-World Evidence.
The Increasing Importance of Rigorous Real-World Evidence.
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DOI：
10.1093/jncics/pkac051
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发表时间：
2022-08-10
影响因子：
4.4
通讯作者：
中科院分区：
文献类型：
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作者：
真实世界的证据来自对真实世界数据的研究，这些数据是从传统临床研究环境之外的多个来源积累的医疗保健信息，包括电子健康记录、医疗索赔和账单数据、产品和疾病登记以及个人设备和健康应用程序。与传统的临床试验相比，真实世界证据研究中使用的数据是从其原始意图（例如，医疗索赔和报销账单数据）重新利用的，或者是为了回答各种研究问题（例如，疾病登记）而建立的。现实世界的证据提供了许多机会来补充从传统临床试验中获得的见解，因为随着健康信息技术和数据汇总的进步，现实世界数据的可用性越来越高，传统试验往往缺乏普遍性，传统试验的成本不断增加。例如，基于人群的观察性研究与随机肿瘤学试验的系统比较发现，两种方法之间的风险比估计值之间没有统计学显著相关性（2）。多种原因导致观察到的差异，包括研究人群差异、数据质量差、研究设计不当、未控制的混杂因素和其他偏倚来源。尽管其中一些原因可能反映了真实世界数据的真实性（即，与必须符合限制性入选和排除标准的临床试验人群相比，真实世界数据通常更能代表真实世界患者人群），但这些差异在历史上导致了关于真实世界证据有效性的问题。考虑到这些问题，Merola et al. (4)使用原则性方法研究了地舒利与亮丙瑞林与主要心血管不良事件（MACE）的相关性，研究者试图模拟或预测临床试验的结果。这种方法涉及在制定方案时预先指定的一系列检查点、方案的预注册以及方案实施后对潜在偏倚来源的额外评估。在目前的研究中，作者特别试图模仿发音
Real-world evidence is derived from studies of real-world data, which are information on health care accumulated from multiple sources outside the traditional clinical research setting, including electronic health records, medical claims and billing data, product and disease registries, and personal devices and health applications (1). In contrast to traditional clinical trials, data used in real-world evidence studies are repurposed from their original intent (eg, medical claims and billing data for reimbursement) or are set up to answer a variety of research questions (eg, disease registries). Real-world evidence presents many opportunities for complementing the insights gained from traditional clinical trials given the increasing availability of real-world data with advancements in health information technology and data aggregation, the frequent lack of generalizability of traditional trials, and the increasing cost of traditional trials.Historically, studies using real-world data have often not recapitulated the results of randomized clinical trials. For instance, a systematic comparison of population-based observational studies with randomized oncology trials found no statistically significant correlation between the hazard ratio estimates between the 2 methods (2). Multiple reasons contribute to the discrepancies observed, including differences in study populations, poor data quality, inappropriate study designs, confounders not controlled for, and other sources of bias. Although some of these reasons may reflect the reality of real-world data (namely, realworld data are often more representative of the real-world patient population compared with clinical trial populations, which must meet restrictive inclusion and exclusion criteria), these discrepancies have historically contributed to questions regarding the validity of real-world evidence (3). With these concerns in mind, Merola et al.(4) studied the association of degarelix vs leuprolide and major adverse cardiovascular events (MACE) using a principled approach where investigators attempt to emulate or predict the results of clinical trials. This approach involves a series of prespecified checkpoints when developing the protocol, preregistration of the protocol, and additional assessment of potential sources of bias after implementation of the protocol. In the current study, the authors specifically attempted to emulate the PRONOUNCE
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