文章基本信息

标题：Non-parametric estimation of survival probabilities with a time-dependent exposure switch: application to (simulated) heart transplant data
本地全文：下载
作者：Davide Paolo Bernasconi ; Maria Grazia Valsecchi ; Laura Antolini 等
期刊名称：Epidemiology, Biostatistics and Public Health
印刷版ISSN：2282-0930
出版年度：2018
卷号：15
期号：3
DOI：10.2427/12963
语种：English
出版社：PREX
其他摘要：Background: To summarize the survival experience of patients waiting for heart transplant and to compare it with the post-transplant survival it is not possible to use the Kaplan-Meier estimator considering the intervention status as fixed in time because of the well known "immortal time bias" issue. Methods: We reviewed and applied to a simulated dataset the available methods to perform a non-parametric analysis accounting for the time-varying nature of the transplant status. Specifically we considered the Simon-Makuch estimator and the recently proposed "clock-back" estimator. Results: We showed that the Simon-Makuch estimator for the survival of patients on list is unbiased but the corresponding estimator of the post-transplant survival is not reliable for non-markov contexts like the one considered. Instead, if the semi-Markov assumption could be postulated (the post-transplant mortality depends mainly on the time since transplant and not on the waiting time to the intervention), the "clock-back" estimator produces valid results. Conclusion: We enlightened the importance of testing the process memory assumptions (e.g. Markov properties) in order to choose the approach more reliable. Moreover, we recommend the use of the Simon-Makuch method to study the survival of patients before the intervention and the use of the "clock back" estimator for the post-intervention survival in semi-markovian contexts.