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Activity Number: 145
Type: Invited
Date/Time: Monday, August 4, 2014 : 10:30 AM to 12:20 PM
Sponsor: ENAR
Abstract #310925 View Presentation
Title: Life Beyond the Logrank Test and Hazard Ratio Estimation in Survival Analysis
Author(s): Hajime Uno*+ and Brian Claggett and Lu Tian and Lee Jen Wei
Companies: Dana-Farber Cancer Institute and Harvard Medical School and Stanford University and Harvard
Keywords: proportional hazards ; robust tests
Abstract:

In medical research the between-group difference with respect to censored time-to-event data is quantified routinely by the hazard ratio, and the qualitative difference is tested by the logrank test, or equivalently the score test based on Cox's proportional hazards (PH) model. When the PH assumption is plausible, the hazard ratio estimate may capture the relative difference between groups, and the logrank test is then the most powerful test to detect the group difference. However, when the PH assumption is violated, the interpretation of the hazard ratio estimate will be rather difficult. Although extensive research has been published in the statistical literature to address the problems of using the hazard ratio as a group contrast measure, those involved in clinical research do not seem to have fully appreciated these concerns. Here, we revisit the issue of the hazard ratio and discuss the limitations of such a model-based summary for the between-group difference. We then discuss clinically interpretable model-free summary measures as alternatives to the hazard ratio. We also present new two-sample hypothesis tests as alternatives to the logrank test.


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