SAGE Journals Online
Advertisement
Sign In to gain access to subscriptions and/or personal tools.

 

Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Advertisement

Sign In to gain access to subscriptions and/or personal tools.
Statistical Methods in Medical Research
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Gamel, J. W
Right arrow Articles by Vogel, R. L
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Gamel, J. W
Right arrow Articles by Vogel, R. L
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Non-parametric comparison of relative versus cause-specific survival in Surveillance, Epidemiology and End Results (SEER) programme breast cancer patients

John W Gamel

Veterans Administration Medical Center and University of Louisville School of Medicine, Louisville, Kentucky, USA, jgamel{at}louisville.edu

Robert L Vogel

Departments of Family Medicine and Community Medicine, Mercer University School of Medicine, Macon, Georgia, USA

Cancer-related mortality can be measured by two dissimilar methods: NAcause-specific survival (based on mortality attributed to a specific cause), and relative survival (based on mortality relative to a matched cohort). We used both methods to determine actuarial survival in a population of 119 502 breast cancer patients from the Surveillance, Epidemiology and End Results (SEER) programme data set, with 20 years of follow-up. The population was divided into four strata by patient age and tumour stage. In all strata, there was only minimal deviation between the two survival methods. Of particular interest was the cause-specific treatment of patients recorded as dead of unknown cause, i.e. those deaths that could not be attributed with certainty to either ‘breast cancer’ or to ‘other causes’. Findings suggest that the most reliable results may be obtained by apportioning these deaths between ‘dead of cause’ and ‘withdrawn at the time of death’. This apportionment is based on the relative number of deaths attributed to ‘breast cancer’ versus ‘other causes’.

Statistical Methods in Medical Research, Vol. 10, No. 5, 339-352 (2001)
DOI: 10.1177/096228020101000503


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?


This article has been cited by other articles:


Home page
J Natl Cancer Inst MonogrHome page
S. B. Clauser
Use of Cancer Performance Measures in Population Health: A Macro-level Perspective
J Natl Cancer Inst Monographs, October 1, 2004; 2004(33): 142 - 154.
[Abstract] [Full Text] [PDF]



Advertisement