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Restricted survival benefit with right‐censored data
Author(s) -
Zhang Shixiao,
LeBlanc Michael L.,
Zhao YingQi
Publication year - 2022
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.202000392
Subject(s) - censoring (clinical trials) , jackknife resampling , statistics , hazard ratio , survival analysis , inference , inverse probability , econometrics , mathematics , empirical likelihood , statistic , medicine , computer science , bayesian probability , confidence interval , estimator , artificial intelligence , posterior probability
The hazard ratio is widely used to quantify treatment effects. However, it may be difficult to interpret for patients and practitioners, especially when the hazard ratio is not constant over time. Alternative measures of the treatment effects have been proposed such as the difference of the restricted mean survival times, the difference in survival proportions at some fixed follow‐up time, or the net chance of a longer survival. In this paper, we propose the restricted survival benefit (RSB), a quantity that can incorporate multiple useful measurements of treatment effects. Hence, it provides a framework for a comprehensive assessment of the treatment effects. We provide estimation and inference procedures for the RSB that accommodate censored survival outcomes, using methods of the inverse‐probability‐censoring‐weighted U $U$ ‐statistic and the jackknife empirical likelihood. We conduct extensive simulation studies to examine the numerical performance of the proposed method, and we analyze data from a randomized Phase III clinical trial (SWOG S0777) using the proposed method.