Department of Statistics and Data Science, Cornell University, Ithaca, NY 14853;
Department of Cardiothoracic Surgery, Weill Cornell Medicine, New York, NY 10021.
Proc Natl Acad Sci U S A. 2021 Dec 7;118(49). doi: 10.1073/pnas.2105254118.
The fragility index is a clinically meaningful metric based on modifying patient outcomes that is increasingly used to interpret the robustness of clinical trial results. The fragility index relies on a concept that explores alternative realizations of the same clinical trial by modifying patient measurements. In this article, we propose to generalize the fragility index to a family of fragility indices called the incidence fragility indices that permit only outcome modifications that are sufficiently likely and provide an exact algorithm to calculate the incidence fragility indices. Additionally, we introduce a far-reaching generalization of the fragility index to any data type and explain how to permit only sufficiently likely modifications for nondichotomous outcomes. All of the proposed methodologies follow the fragility index concept.
脆弱指数是一种基于修正患者结局的有临床意义的指标，越来越多地被用于解释临床试验结果的稳健性。脆弱指数依赖于一个概念，即通过修改患者测量值来探索同一临床试验的替代实现。在本文中，我们提出将脆弱指数推广到一类称为发生率脆弱指数的脆弱指数家族，这些指数只允许进行足够可能的结局修正，并提供了一种精确的算法来计算发生率脆弱指数。此外，我们还将脆弱指数推广到任何数据类型，并解释了如何仅允许对非二分类结局进行足够可能的修正。所有提出的方法都遵循脆弱指数的概念。
