期刊
JOURNAL OF THE AMERICAN COLLEGE OF CARDIOLOGY
卷 82, 期 14, 页码 1445-1463出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.jacc.2023.07.024
关键词
heart failure; recurrent events; statistics; trial design
Many randomized trials in cardiovascular disease focus on time-to-first event as the primary outcome, but repeat nonfatal events often occur during patient follow-up. This article explores the value of including repeat events in the analysis, compares different statistical methods for analyzing repeat events, and provides recommendations for future trials based on their performance in cardiovascular trials and heart failure trials.
Many randomized trials in cardiovascular disease have repeat nonfatal events (such as hospitalizations) occurring during patient follow-up; yet, it remains common practice to have time-to-first event as the primary outcome. We explore the value of analyses that include repeat events. Do they help us understand the effect of treatment and total disease burden? Do they enhance statistical power? Should they become a trial's primary analysis? It may also be difficult to choose which of the various statistical methods for analyzing repeat events to use, and we provide a nontechnical guide to what each method is doing. We compare several methods for repeat events: Lin Wei Yang Ying, negative binomial, joint frailty, win ratio, and area under the curve. We illustrate their performance in 5 large cardiovascular trials and compare them with time-to-first-event analyses. We review their use in recently published heart failure trials and make recommendations for their use in future trials.(c) 2023 by the American College of Cardiology Foundation.
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