Alternative Analysis Methods for Time to Event Endpoints under Non-proportional Hazards: A Comparative Analysis

• Published in: arXiv.org 2019-09
• Main Authors: Lin, Ray S, Lin, Ji, Roychoudhury, Satrajit, Anderson, Keaven M, Hu, Tianle, Huang, Bo, Leon, Larry F, Liao, Jason JZ, Liu, Rong, Luo, Xiaodong, Mukhopadhyay, Pralay, Qin, Rui, Tatsuoka, Kay, Wang, Xuejing, Wang, Yang, Zhu, Jian, Tai-Tsang, Chen, Iacona, Renee, Cross-Pharma Non-proportional Hazards Working Group
• Format: Article
• Language: English
• Subjects: Hazards; Rank tests; Sensitivity analysis
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1909.09467

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, RMST), 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 estimates 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 PH or non-PH patterns, the MaxCombo test is relatively robust across patterns. Since the treatment effect changes overtime 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 pre-specified as sensitivity analyses to evaluate the totality of the data.