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Workshop in Biostatistics presents "Adaptive long-term restricted mean survival time approach to compare time-to-event outcomes in randomized controlled trials for immunotherapy"

Topic: 
Adaptive long-term restricted mean survival time approach to compare time-to-event outcomes in randomized controlled trials for immunotherapy
Thursday, February 13, 2020 - 1:30pm
Venue: 
LKSC 120
Speaker: 
Prof. Hajime Uno (Harvard Medical School)
Abstract / Description: 

Logrank/hazard ratio (HR) test/estimation approach has been routinely used in almost all cancer clinical trials with time-to-event outcomes. Although the logrank test is an asymptotically valid nonparametric test, it is not the most powerful test when the pattern of the difference is non-proportional hazards (PH). Also, interpretation of the HR is not obvious when the PH assumption does not hold. For immunotherapy trials, we often see a delayed difference pattern, where the conventional logrank/HR approach is not appropriate for testing equality nor estimating the magnitude of the treatment effect. Restricted mean survival time (RMST)-based analysis has been proposed as an alternative to the logrank/HR approach. It provides a robust and interpretable summary of the treatment effect. However, it is known that the standard RMST-based approach offers lower power than the logrank/HR approach in delayed difference scenarios. We propose a new prespecified RMST-based test and a corresponding treatment effect estimation procedure, particularly when a delayed difference pattern is expected at the design stage. Simulation studies show how effectively the proposed method can detect the treatment difference, compared to the logrank test, various weighted logrank tests, MaxCombo test, standard RMST-based tests, and so on.The Workshop is held from 1:30-2:50pm in Medical School Office Building (MSOB), Rm x303, 1265 Welch Road, Stanford, unless otherwise specified on the calendar at the link below.