Simulation-based sample size calculations of marginal proportional means models for recurrent events with competing risks.

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY Pharmaceutical Statistics Pub Date : 2024-03-20 DOI:10.1002/pst.2382
Julie Funch Furberg, Per Kragh Andersen, Thomas Scheike, Henrik Ravn
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Abstract

In randomised controlled trials, the outcome of interest could be recurrent events, such as hospitalisations for heart failure. If mortality rates are non-negligible, both recurrent events and competing terminal events need to be addressed when formulating the estimand and statistical analysis is no longer trivial. In order to design future trials with primary recurrent event endpoints with competing risks, it is necessary to be able to perform power calculations to determine sample sizes. This paper introduces a simulation-based approach for power estimation based on a proportional means model for recurrent events and a proportional hazards model for terminal events. The simulation procedure is presented along with a discussion of what the user needs to specify to use the approach. The method is flexible and based on marginal quantities which are easy to specify. However, the method introduces a lack of a certain type of dependence. This is explored in a sensitivity analysis which suggests that the power is robust in spite of that. Data from a randomised controlled trial, LEADER, is used as the basis for generating data for a future trial. Finally, potential power gains of recurrent event methods as opposed to first event methods are discussed.

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基于边际比例均值模型的模拟样本量计算,适用于具有竞争风险的复发性事件。
在随机对照试验中,感兴趣的结果可能是复发事件,如心力衰竭住院。如果死亡率不可忽略,那么在制定估计值时就需要同时考虑复发事件和竞争性终末事件,统计分析也不再是小事。为了设计未来以具有竞争风险的复发事件为主要终点的试验,有必要进行功率计算以确定样本大小。本文介绍了一种基于模拟的功率估算方法,该方法以复发性事件的比例均值模型和终末事件的比例危险模型为基础。本文介绍了模拟程序,并讨论了用户在使用该方法时需要说明的事项。该方法非常灵活,基于边际量,易于指定。然而,该方法缺乏某种类型的依赖性。敏感性分析对此进行了探讨,结果表明,尽管如此,该方法仍具有很强的有效性。随机对照试验 LEADER 的数据被用作生成未来试验数据的基础。最后,还讨论了与首次事件法相比,经常事件法的潜在功率增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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