Premium
Restricted mean survival time as a summary measure of time‐to‐event outcome
Author(s) -
Hasegawa Takahiro,
Misawa Saori,
Nakagawa Shintaro,
Tanaka Shinichi,
Tanase Takanori,
Ugai Hiroyuki,
Wakana Akira,
Yodo Yasuhide,
Tsuchiya Satoru,
Suganami Hideki
Publication year - 2020
Publication title -
pharmaceutical statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 38
eISSN - 1539-1612
pISSN - 1539-1604
DOI - 10.1002/pst.2004
Subject(s) - event (particle physics) , sample size determination , statistics , outcome (game theory) , time point , mathematics , survival analysis , hazard ratio , econometrics , confidence interval , mathematical economics , physics , philosophy , quantum mechanics , aesthetics
Summary Many clinical research studies evaluate a time‐to‐event outcome, illustrate survival functions, and conventionally report estimated hazard ratios to express the magnitude of the treatment effect when comparing between groups. However, it may not be straightforward to interpret the hazard ratio clinically and statistically when the proportional hazards assumption is invalid. In some recent papers published in clinical journals, the use of restricted mean survival time (RMST) or τ ‐year mean survival time is discussed as one of the alternative summary measures for the time‐to‐event outcome. The RMST is defined as the expected value of time to event limited to a specific time point corresponding to the area under the survival curve up to the specific time point. This article summarizes the necessary information to conduct statistical analysis using the RMST, including the definition and statistical properties of the RMST, adjusted analysis methods, sample size calculation, information fraction for the RMST difference, and clinical and statistical meaning and interpretation. Additionally, we discuss how to set the specific time point to define the RMST from two main points of view. We also provide developed SAS codes to determine the sample size required to detect an expected RMST difference with appropriate power and reconstruct individual survival data to estimate an RMST reference value from a reported survival curve.