Alternative Analysis Methods for Time to Event Endpoints Under Nonproportional Hazards: A Comparative Analysis. (2nd April 2020)

• Record Type: Journal Article
• Authors: Lin, Ray S.; Lin, Ji; Roychoudhury, Satrajit; Anderson, Keaven M.; Hu, Tianle; Huang, Bo; Leon, Larry F; Liao, Jason J.Z.; Liu, Rong; Luo, Xiaodong; Mukhopadhyay, Pralay; Qin, Rui; Tatsuoka, Kay; Wang, Xuejing; Wang, Yang; Zhu, Jian; Chen, Tai-Tsang; Iacona, Renee
• Is Part Of: Statistics in biopharmaceutical research. Volume 12:Number 2(2020)
• Page Start: 187
• Page End: 198
• Publication Date: 2020-04-02
• Subjects: Fleming–Harrington test -- Log-rank test -- Nonproportional hazards -- Oncology trial -- Survival analysis; Pharmacy -- Statistical methods -- Periodicals; Pharmaceutical biotechnology -- Statistical methods -- Periodicals; Biopharmaceutics -- Periodicals; Biometry -- Periodicals; Pharmacy -- Statistical methods; Periodicals; 615.190727
• DOI: 10.1080/19466315.2019.1697738
• Languages: English
• ISSNs: 1946-6315

Abstract

Abstract: The log-rank test is most powerful under proportional hazards (PH). In practice, non-PH patterns are often observed in clinical trials, such as in immuno-oncology; therefore, alternative methods are needed to restore the efficiency of statistical testing. Three categories of testing methods were evaluated, including weighted log-rank tests, Kaplan–Meier curve-based tests (including weighted Kaplan–Meier and restricted mean survival time), and combination tests (including Breslow test, Lee's combo test, and MaxCombo test). Nine scenarios representing the PH and various non-PH patterns were simulated. The power, Type I error, and effect estimate of each method were compared. In general, all tests control Type I error well. There is not a single most powerful test across all scenarios. In the absence of prior knowledge regarding the underlying or non-PH patterns, the MaxCombo test is relatively robust across patterns. Since the treatment effect changes over time under non-PH, the overall profile of the treatment effect may not be represented comprehensively based on a single measure. Thus, multiple measures of the treatment effect should be prespecified as sensitivity analyses to describe the totality of the data. Supplementary materials for this article are available online.