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Licensed Unlicensed Requires Authentication Published by De Gruyter November 29, 2013

Comparison of restricted mean survival times between treatments based on a stratified Cox model

  • Xu Zhang EMAIL logo

Abstract

Causal inference in survival analysis has been centered on treatment effect assessment with adjustment of covariates. The direct adjustment method is usually employed to find the survival function of a treatment. A Cox model that stratifies the cumulative hazard by treatment is an ideal choice for performing direct adjustment because the treatment effects are allowed to vary over time. A SAS macro was developed to implement comparison of direct adjusted survivals between treatments at a selected time point. The restricted mean survival time can be derived from a direct adjusted survival function. This statistic summarizes the survival outcome of a treatment. Comparison of restricted means provides assessment of treatment effect over a time interval. The first aim of this article was to provide an overview of the restricted mean survival time. The second aim was to introduce a SAS macro that computes the restricted mean survival times from direct adjusted survivals based on a stratified Cox model. Data preparation and macro invocation are illustrated in an analysis of survival data involving three types of stem cell transplants.


Corresponding author: Xu Zhang, Center of Biostatistics and Bioinformatics, Cancer Institute, University of Mississippi Medical Center, 2500 North State Street, Jackson, MI 39216, USA, E-mail:

The author thanks Ms. Mary Manuel for reading the manuscript. Her valuable comments helped the author to improve the manuscript.

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Received: 2013-6-23
Accepted: 2013-10-22
Published Online: 2013-11-29
Published in Print: 2013-12-01

©2013 by Walter de Gruyter Berlin Boston

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