Window mean survival time. (13th July 2021)

• Record Type: Journal Article
• Authors: Paukner, Mitchell; Chappell, Richard
• Is Part Of: Statistics in medicine. Volume 40:Number 25(2021)
• Page Start: 5521
• Page End: 5533
• Publication Date: 2021-07-13
• Subjects: logrank test -- nonproportional hazards -- survival data -- weighted rank test; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.9138
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : We propose a class of alternative estimates and tests to restricted mean survival time (RMST) which improves power in numerous survival scenarios while maintaining a level of interpretability. The industry standards for interpretable hypothesis tests in survival analysis, RMST and logrank tests (LRTs), can suffer from low power in cases where the proportional hazards assumption fails. In particular, when late differences occur between survival curves, our proposed estimate and class of tests, window mean survival time (WMST), outperforms both RMST and LRT without sacrificing interpretability, unlike weighted rank tests (WRTs). WMST has the added advantage of maintaining high power when the proportional hazards assumption is met, while WRTs do not. With testing methods often being chosen in advance of data collection, WMST can ensure adequate power without distributional assumptions and is robust to the choice of its restriction parameters. Functions for performing WMST analysis are provided in the survWM2 package in R.