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心血管试验中使用胜率的谬误:挑战与解决方案

Fallacies of Using the Win Ratio in Cardiovascular Trials: Challenges and Solutions.

作者信息

Ajufo Ezimamaka, Nayak Aditi, Mehra Mandeep R

机构信息

Center for Advanced Heart Disease, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

出版信息

JACC Basic Transl Sci. 2023 Jun 26;8(6):720-727. doi: 10.1016/j.jacbts.2023.05.004. eCollection 2023 Jun.

Abstract

The win ratio was introduced into cardiovascular trials as a potentially better way of analyzing composite endpoints to account for the hierarchy of clinical significance of their components and to facilitate the inclusion of recurrent events. The basic concept of the win ratio is to define a hierarchy of clinical importance within the components of the composite outcome, form all possible pairs by comparing every subject in the treatment group with every subject in the control group, and then evaluate each pair for the occurrence of the components of the composite outcome in descending order of importance, starting at the most important and progressing down the hierarchy if the outcome does not result in a win in either pair until pairs are tied for the outcome after exhaustion of all components. Although the win ratio offers a novel method of depiction of outcomes in clinical trials, its advantages may be counterbalanced by several fallacies (such as ignoring ties and weighting each hierarchal component equally) and challenges in appropriate clinical interpretation (establishing clinical meaningfulness of the observed effect size). From this perspective, we discuss these and other fallacies and provide a suggested framework to overcome such limitations to enhance utility of this statistical method across the clinical trial enterprise.

摘要

胜率被引入心血管试验,作为一种分析复合终点的潜在更好方法,以考虑其组成部分临床意义的层次结构,并便于纳入复发事件。胜率的基本概念是在复合结局的组成部分内定义临床重要性的层次结构,通过将治疗组中的每个受试者与对照组中的每个受试者进行比较形成所有可能的配对,然后按照重要性降序评估每对中复合结局组成部分的发生情况,从最重要的开始,如果在任何一对中结局都没有导致获胜,则沿着层次结构向下推进,直到所有组成部分都用尽后各对在结局上打成平手。尽管胜率为临床试验中的结局描绘提供了一种新颖的方法,但其优势可能会被一些谬误(如忽略平手情况并平等加权每个层次组成部分)以及适当临床解释方面的挑战(确定观察到的效应大小的临床意义)所抵消。从这个角度出发,我们讨论这些及其他谬误,并提供一个建议框架以克服此类限制,从而提高这种统计方法在整个临床试验领域的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e06b/10322884/3f7fe0e75ca2/fx1.jpg

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