The fragility index can be used for sample size calculations in clinical trials

被引:29
作者
Baer, Benjamin R. [1 ]
Gaudino, Mario [2 ]
Fremes, Stephen E. [3 ]
Charlson, Mary [4 ]
Wells, Martin T. [1 ,4 ]
机构
[1] Cornell Univ, Dept Stat & Data Sci, Ithaca, NY 14850 USA
[2] Weill Cornell Med, Dept Cardiothorac Surg, New York, NY USA
[3] Univ Toronto, Sunnybrook Hlth Sci, Schulich Heart Ctr, Toronto, ON, Canada
[4] Weill Cornell Med, Dept Med, New York, NY USA
关键词
Fragility index; P value; Statistical significance; Research methods; Sample size calculation; Trial design; STATISTICALLY SIGNIFICANT FINDINGS; RANDOMIZED-TRIALS; P-VALUE; SURGERY;
D O I
10.1016/j.jclinepi.2021.08.010
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
Objective:The fragility index is a clinically interpretable metric increasingly used to interpret the robustness of clinical trials results that is generally not incorporated in sample size calculation and applied post-hoc. In this manuscript, we propose to base the sample size calculation on the fragility index in a way that supplements the classical prefixed alpha and power cutoffs and we provide a dedicated R software package for the design and analysis tools. Study design and setting: This approach follows from a novel hypothesis testing framework that is based on the fragility index and builds on the classical testing approach. As case studies, we re-analyse the design of two important trials in cardiovascular medicine, the FAME and FAMOUS-NSTEMI trials. Results: The analyses show that approach returns sample sizes which results in a higher power for the P value based test and most importantly a lower and context dependent Type I error rate for the fragility index based test compared to standard tests. Conclusion: Our method allows clinicians to control for the fragility index during clinical trial design. (C) 2021 Elsevier Inc. All rights reserved.
引用
收藏
页码:199 / 209
页数:11
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