将随机试验的相对效应汇总指标迁移至接受治疗的患者人群：在乳腺癌内分泌治疗中的应用
Transporting summary measures of relative effects from randomised trials to the treated patient population: an application to breast cancer endocrine therapy
- University of Oxford（牛津大学）
- University of North Carolina at Chapel Hill（北卡罗来纳大学教堂山分校）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究提出结合常规诊疗数据与随机试验汇总效应指标，估计接受治疗者的绝对治疗效果（ATT），并应用于乳腺癌内分泌治疗，以支持临床决策。
AI中文摘要：
随机试验通常报告试验人群的相对治疗效果，如风险比和风险比。然而，临床决策往往受益于对符合治疗条件人群的绝对治疗效果估计。试验参与者可能无法很好地代表这一目标人群，且对个体参与者试验数据访问的限制可能进一步使绝对效应估计复杂化。常规诊疗数据通常能代表目标人群，但可能受到未控制的混杂影响。我们考虑通过将接受治疗的常规诊疗患者的代表性样本与来自随机试验或试验荟萃分析的汇总指标（即估计的风险比或风险比）相结合，来估计接受治疗者的平均治疗效果（ATT），这是一种绝对度量。在边际或条件可迁移性假设下，ATT被证明是可识别的。讨论了效应测量可折叠性对可迁移性的影响，并提出了ATT的插入估计量。模拟研究用于评估估计量在各种场景下的有限样本性能。所提出的方法被应用于使用随机试验荟萃分析结果和英格兰国家疾病登记服务的数据，估计内分泌治疗对15年乳腺癌死亡率的ATT。
英文摘要：
Randomised trials often report relative treatment effects, such as risk ratios and hazard ratios, for trial populations. Clinical decision-making, however, often benefits from estimates of absolute treatment effects in the population eligible for treatment. Trial participants may not represent this target population well, and restrictions on access to individual participant trial data can further complicate absolute effect estimation. Routine care data are often representative of the target population but may be subject to uncontrolled confounding. We consider estimation of the average treatment effect on the treated (ATT), an absolute measure, by combining a representative sample of treated routine care patients with summary measures (i.e., estimated risk or hazard ratios) from either a randomised trial or a meta-analysis of trials. Under marginal or conditional transportability assumptions, the ATT is shown to be identifiable. The implications of collapsibility of the effect measure on transportability are discussed, and plug-in estimators of the ATT are presented. Simulation studies are used to assess finite sample performance of the estimators in a range of settings. The proposed methods are applied to estimate the ATT of endocrine therapy on 15-year breast cancer mortality using results from a meta-analysis of randomised trials and England's National Disease Registration Service.
