Happich Michael, Brnabic Alan, Faries Douglas, Abrams Keith, Winfree Katherine B, Girvan Allicia, Jonsson Pall, Johnston Joseph, Belger Mark
Lilly Research Centre, Eli Lilly and Company, Surrey, UK.
Eli Lilly and Company, Sydney, New South Wales, Australia.
Clin Pharmacol Ther. 2020 Oct;108(4):817-825. doi: 10.1002/cpt.1854. Epub 2020 May 30.
Evidence from randomized controlled trials available for timely health technology assessments of new pharmacological treatments and regulatory decision making may not be generalizable to local patient populations, often resulting in decisions being made under uncertainty. In recent years, several reweighting approaches have been explored to address this important question of generalizability to a target population. We present a case study of the Innovative Medicines Initiative to illustrate the inverse propensity score reweighting methodology, which may allow us to estimate the expected treatment benefit if a clinical trial had been run in a broader real-world target population. We learned that identifying treatment effect modifiers, understanding and managing differences between patient characteristic data sets, and balancing the closeness of trial and target patient populations with effective sample size are key to successfully using this methodology and potentially mitigating some of this uncertainty around local decision making.
可用于新药理学治疗的及时卫生技术评估和监管决策的随机对照试验证据，可能无法推广到当地患者群体，这常常导致在不确定性情况下做出决策。近年来，人们探索了几种重新加权方法来解决这个关于对目标人群的可推广性的重要问题。我们展示了创新药物倡议的一个案例研究，以说明逆倾向评分重新加权方法，该方法可能使我们能够估计如果在更广泛的真实世界目标人群中进行临床试验，预期的治疗益处。我们了解到，识别治疗效果修饰因素、理解和管理患者特征数据集之间的差异，以及用有效样本量平衡试验和目标患者群体的接近程度，是成功使用该方法并可能减轻当地决策中一些不确定性的关键。
