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arXiv · 1909.09467

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

Ray S. Lin·Ji Lin·Satrajit Roychoudhury·Keaven M. Anderson·Tianle Hu·Bo Huang·Larry F Leon·Jason JZ Liao·Rong Liu·Xiaodong Luo·Pralay Mukhopadhyay·Rui Qin·Kay Tatsuoka·Xuejing Wang·Yang Wang·Jian Zhu·Tai-Tsang Chen·Renee Iacona·Cross-Pharma Non-proportional Hazards Working Group
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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, 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.

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Ray S. Lin, Ji Lin, Satrajit Roychoudhury, Keaven M. Anderson, Tianle Hu, Bo Huang, Larry F Leon, Jason JZ Liao, Rong Liu, Xiaodong Luo, Pralay Mukhopadhyay, Rui Qin, Kay Tatsuoka, Xuejing Wang, Yang Wang, Jian Zhu, Tai-Tsang Chen, Renee Iacona, Cross-Pharma Non-proportional Hazards Working Group. 2019-09-20. Alternative Analysis Methods for Time to Event Endpoints under Non-proportional Hazards: A Comparative Analysis. https://doi.org/10.1080/19466315.2019.1697738

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