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On the empirical choice of the time window for restricted mean survival time
Author(s) -
Tian Lu,
Jin Hua,
Uno Hajime,
Lu Ying,
Huang Bo,
Anderson Keaven M.,
Wei LJ
Publication year - 2020
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.13237
Subject(s) - censoring (clinical trials) , statistics , inference , survival analysis , mathematics , econometrics , accelerated failure time model , computer science , artificial intelligence
The t ‐year mean survival or restricted mean survival time (RMST) has been used as an appealing summary of the survival distribution within a time window [0, t ]. RMST is the patient's life expectancy until time t and can be estimated nonparametrically by the area under the Kaplan‐Meier curve up to t . In a comparative study, the difference or ratio of two RMSTs has been utilized to quantify the between‐group‐difference as a clinically interpretable alternative summary to the hazard ratio. The choice of the time window [0, t ] may be prespecified at the design stage of the study based on clinical considerations. On the other hand, after the survival data have been collected, the choice of time point t could be data‐dependent. The standard inferential procedures for the corresponding RMST, which is also data‐dependent, ignore this subtle yet important issue. In this paper, we clarify how to make inference about a random “parameter.” Moreover, we demonstrate that under a rather mild condition on the censoring distribution, one can make inference about the RMST up to t , where t is less than or even equal to the largest follow‐up time (either observed or censored) in the study. This finding reduces the subjectivity of the choice of t empirically. The proposal is illustrated with the survival data from a primary biliary cirrhosis study, and its finite sample properties are investigated via an extensive simulation study.