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广义成对比较评估治疗效果:JACC 综述专题的一周。

Generalized Pairwise Comparisons to Assess Treatment Effects: JACC Review Topic of the Week.

机构信息

Data Science Institute, Interuniversity Institute for Biostatistics and statistical Bioinformatics (I-Biostat), University of Hasselt, Hasselt, Belgium.

International Drug Development Institute, Louvain-la-Neuve, Belgium.

出版信息

J Am Coll Cardiol. 2023 Sep 26;82(13):1360-1372. doi: 10.1016/j.jacc.2023.06.047.

Abstract

A time-to-first-event composite endpoint analysis has well-known shortcomings in evaluating a treatment effect in cardiovascular clinical trials. It does not fully describe the clinical benefit of therapy because the severity of the events, events repeated over time, and clinically relevant nonsurvival outcomes cannot be considered. The generalized pairwise comparisons (GPC) method adds flexibility in defining the primary endpoint by including any number and type of outcomes that best capture the clinical benefit of a therapy as compared with standard of care. Clinically important outcomes, including bleeding severity, number of interventions, and quality of life, can easily be integrated in a single analysis. The treatment effect in GPC can be expressed by the net treatment benefit, the success odds, or the win ratio. This review provides guidance on the use of GPC and the choice of treatment effect measures for the analysis and reporting of cardiovascular trials.

摘要

时间至首次事件复合终点分析在评估心血管临床试验的治疗效果方面存在明显的局限性。它不能完全描述治疗的临床获益,因为事件的严重程度、随时间重复的事件以及临床相关的非生存结局都无法考虑在内。广义成对比较(GPC)方法通过纳入任何数量和类型的最能捕捉治疗临床获益的结局,从而在定义主要终点方面增加了灵活性,与标准治疗相比。包括出血严重程度、干预次数和生活质量在内的重要临床结局可以很容易地整合在单个分析中。GPC 中的治疗效果可以用净治疗效益、成功几率或赢率来表示。本文综述了 GPC 的使用以及治疗效果指标的选择,以用于心血管试验的分析和报告。

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