Literature DB >> 17850917

A SAS macro for estimation of direct adjusted survival curves based on a stratified Cox regression model.

Xu Zhang1, Fausto R Loberiza, John P Klein, Mei-Jie Zhang.   

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.

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Year:  2007        PMID: 17850917     DOI: 10.1016/j.cmpb.2007.07.010

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  128 in total

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2.  SAS macros for estimation of direct adjusted cumulative incidence curves under proportional subdistribution hazards models.

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Journal:  Comput Methods Programs Biomed       Date:  2010-08-17       Impact factor: 5.428

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4.  Contemporary trends in heart failure with reduced and preserved ejection fraction after myocardial infarction: a community study.

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Journal:  Haematologica       Date:  2016-02-11       Impact factor: 9.941

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Journal:  CMAJ Open       Date:  2017-03-28

7.  Caregiving strain and all-cause mortality: evidence from the REGARDS study.

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8.  Association of Second-line Antidiabetic Medications With Cardiovascular Events Among Insured Adults With Type 2 Diabetes.

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Journal:  JAMA Netw Open       Date:  2018-12-07

9.  Graft-versus-host disease and survival after cord blood transplantation for acute leukemia: a comparison of Japanese versus White populations.

Authors:  Yachiyo Kuwatsuka; Yoshiko Atsuta; Mary M Horowitz; Jiro Inagaki; Junya Kanda; Koji Kato; Katsuyoshi Koh; Mei-Jie Zhang; Mary Eapen
Journal:  Biol Blood Marrow Transplant       Date:  2014-02-10       Impact factor: 5.742

10.  Prediagnosis soy food consumption and lung cancer survival in women.

Authors:  Gong Yang; Xiao-Ou Shu; Hong-Lan Li; Wong-Ho Chow; Wanqing Wen; Yong-Bing Xiang; Xianglan Zhang; Hui Cai; Bu-Tian Ji; Yu-Tang Gao; Wei Zheng
Journal:  J Clin Oncol       Date:  2013-03-25       Impact factor: 44.544

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