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利用真实世界数据从随机对照试验中推断证据。

Using Real-World Data to Extrapolate Evidence From Randomized Controlled Trials.

机构信息

Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Market Access, Bayer AG, Wuppertal, Germany.

出版信息

Clin Pharmacol Ther. 2019 May;105(5):1156-1163. doi: 10.1002/cpt.1210. Epub 2018 Sep 24.

Abstract

Randomized controlled trials (RCTs) provide evidence for regulatory agencies, shape clinical practice, influence formulary decisions, and have important implications for patients. However, many patient groups that are major consumers of drugs are under-represented in randomized trials. We review three methods to extrapolate evidence from trial participants to different target populations following market approval and discuss how these could be implemented in practice to support regulatory and health technology assessment decisions. Although these methods are not a substitute for less restrictive pre-approval RCTs or rigorous observational studies when sufficient data are available in the post-approval setting, they can help to fill the evidence gap that exists in the early marketing period. Early evidence using real-world data and methods for extrapolating evidence should be reported with clear explanation of assumptions and limitations especially when used to support regulatory and health technology assessment decisions.

摘要

随机对照试验(RCTs)为监管机构提供证据,影响临床实践、处方决策,并对患者产生重要影响。然而,在 RCT 中,许多主要药物消费者的患者群体代表性不足。我们回顾了三种在市场批准后从试验参与者外推证据到不同目标人群的方法,并讨论了如何在实践中实施这些方法,以支持监管和卫生技术评估决策。尽管这些方法在获得批准后,如果有足够的数据,不能替代限制较少的预先批准的 RCT 或严格的观察性研究,但它们可以帮助填补早期营销期间存在的证据空白。使用真实世界数据和外推证据的方法的早期证据应明确解释假设和局限性,并在用于支持监管和卫生技术评估决策时特别报告。

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