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A SAS macro for estimation of direct adjusted survival curves based on a stratified Cox regression model. Comput Methods Programs Biomed 2007 Nov;88(2):95-101

Date

09/14/2007

Pubmed ID

17850917

DOI

10.1016/j.cmpb.2007.07.010

Scopus ID

2-s2.0-35348887755 (requires institutional sign-in at Scopus site)   246 Citations

Abstract

Often in biomedical research the aim of a study is to compare the outcomes of several treatment arms while adjusting for multiple clinical prognostic factors. In this paper we focus on computation of the direct adjusted survival curves for different treatment groups based on an unstratified or a stratified Cox model. The estimators are constructed by taking the average of the individual predicted survival curves. The method of direct adjustment controls for possible confounders due to an imbalance of patient characteristics between treatment groups. This adjustment is especially useful for non-randomized studies. We have written a SAS macro to estimate and compare the direct adjusted survival curves. We illustrate the SAS macro through the examples analyzing stem cell transplant data and Ewing's sarcoma data.

Author List

Zhang X, Loberiza FR, Klein JP, Zhang MJ

Author

Mei-Jie Zhang PhD Professor in the Institute for Health and Equity department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Biomedical Research
Humans
Proportional Hazards Models
Sarcoma, Ewing
Survival Analysis
United States