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Activity Number: 654
Type: Contributed
Date/Time: Thursday, August 4, 2016 : 8:30 AM to 10:20 AM
Sponsor: Biometrics Section
Abstract #319669 View Presentation
Title: Generalized Estimating Equations for Restricted Mean Survival Time Under General Censoring Mechanisms
Author(s): Xin Wang* and Douglas Schaubel
Companies: University of Michigan and University of Michigan
Keywords: dependent censoring ; generalized estimating equation ; inverse weight ; restricted mean survival time ; pre-treatment survival

Restricted mean survival time (RMST) is often of great clinical interest in practice. Several existing methods involve explicitly projecting out patient-specific survival curves using parameters estimated through Cox regression. However, it would often be preferable to directly model the restricted mean for convenience and in order to yield more directly interpretable covariate effects. We propose generalized estimating equation methods to model RMST as a function of baseline covariates. The proposed methods avoid potentially problematic distributional assumptions pertaining to restricted survival time. Unlike existing methods, we allow censoring to depend on both baseline and time-dependent factors. Large sample properties of the proposed estimators are derived and simulation studies are conducted to assess their finite sample performance. We apply the proposed methods to model RMST in the absence of liver transplantation among end-stage liver disease (ESLD) patients. This analysis requires accommodation for dependent censoring since pre-transplant mortality is dependently censored by the receipt of a liver transplant.

Authors who are presenting talks have a * after their name.

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