| Literature DB >> 32061098 |
Lu Tian1, Hua Jin2, Hajime Uno3, Ying Lu1, Bo Huang4, Keaven M Anderson5, L J Wei6.
Abstract
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.Entities:
Keywords: Kaplan-Meier estimator; RMST; hazard ratio; logrank test
Mesh:
Year: 2020 PMID: 32061098 PMCID: PMC8687138 DOI: 10.1111/biom.13237
Source DB: PubMed Journal: Biometrics ISSN: 0006-341X Impact factor: 2.571