Furberg Julie K, Andersen Per K, Korn Sofie, Overgaard Morten, Ravn Henrik
Biostatistics GLP-1 and CV 1, Novo Nordisk A/S, Vandtårnsvej 114, Søborg, Denmark.
Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark.
Lifetime Data Anal. 2023 Apr;29(2):256-287. doi: 10.1007/s10985-021-09533-5. Epub 2021 Nov 5.
The analysis of recurrent events in the presence of terminal events requires special attention. Several approaches have been suggested for such analyses either using intensity models or marginal models. When analysing treatment effects on recurrent events in controlled trials, special attention should be paid to competing deaths and their impact on interpretation. This paper proposes a method that formulates a marginal model for recurrent events and terminal events simultaneously. Estimation is based on pseudo-observations for both the expected number of events and survival probabilities. Various relevant hypothesis tests in the framework are explored. Theoretical derivations and simulation studies are conducted to investigate the behaviour of the method. The method is applied to two real data examples. The bivariate marginal pseudo-observation model carries the strength of a two-dimensional modelling procedure and performs well in comparison with available models. Finally, an extension to a three-dimensional model, which decomposes the terminal event per death cause, is proposed and exemplified.
在存在终末事件的情况下对复发事件进行分析需要特别关注。对于此类分析,已经提出了几种方法,要么使用强度模型,要么使用边际模型。在对照试验中分析治疗对复发事件的影响时,应特别关注竞争性死亡及其对解释的影响。本文提出了一种同时为复发事件和终末事件构建边际模型的方法。估计基于事件预期数量和生存概率的伪观测值。探索了该框架内的各种相关假设检验。进行了理论推导和模拟研究以考察该方法的性能。该方法应用于两个实际数据示例。双变量边际伪观测模型具有二维建模过程的优势,与现有模型相比表现良好。最后,提出并举例说明了扩展到三维模型的情况,该模型按死亡原因分解终末事件。