The effect of age, race, tumor size, tumor grade, and disease stage on invasive ductal breast cancer survival in the U.S. SEER database
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Purpose. To examine the effect of patient and tumor characteristics on breast cancer survival as recorded in the U.S. National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database from 1973 to 1998.
Methods. A sample of 72,367 female cases from 1973 to 1998 aged 21-- 90 years with invasive ductal breast cancer were examined with Cox proportional hazards regression to determine the effect of age at diagnosis, race, tumor size, tumor grade, disease stage, and year of diagnosis on disease-specific survival.
Results. Larger tumor size and higher tumor grade were found to have large negative effects on survival. Blacks had a 47 % greater risk of death than whites. Year of diagnosis had a positive effect, with a 15 % reduction in risk for each decade in the time period under study. The effects of patient age and disease stage violated the proportional hazards assumption, with distant disease having much poorer short-term survival than one would expect from a proportional hazards model, and younger age groups matching or even falling below the survival rate of the oldest group over time.
Conclusion. Tumor size, grade, race, and year of diagnosis all have significant constant effects on disease-specific survival in breast cancer, while the effects of age at diagnosis and disease stage have significant effects that vary over time.
KeywordsCox regression ductal carcinoma invasive breast cancer proportional hazards SEER
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- Surveillance, Epidemiology, and End Results (SEER) Program (www.seer.cancer.gov) Public-Use Data (1973–1998), National Cancer Institute, DCCPS, Surveillance Research Program, Cancer Statistics Branch, released April 2001, based on the November 2000 submission.Google Scholar
- Cox, D 1972Regression models and life-tables (with discussion)J Royal Stat Soc B34187220Google Scholar
- McCready, D, Chapman, J, Hanna, W, Kalm, H, Murray, D, Fish, E, Trudeau, M, Andrulis, I, Lickley, H 2000Factors affecting distant disease-free survival for primary invasive breast cancer: use of a log-normal model.Ann Surg Oucol7416426Google Scholar
- Hilsenbeck, S, Ravdin, P, de Moor, C, Chamness, G, Osborne, C, Clark, G 1998Time-dependence of hazard ratios for prognostic factors in primary breast cancerBreast Cancer Res and Treat52227237Google Scholar
- Schoenfeld, D 1980Chi-squared goodness-of-fit tests for the proportional hazards regression modelBiometrika67145153Google Scholar
- Grambsch, P, Therneau, T 1994Proportional hazards tests and diagnostics based on weighted residualsBiometrika81515526Google Scholar
- Cox D, Snell E: A general definition of residuals (with discussion), J Royal Stat Soc A 30: 248–275, 1968.Google Scholar
- Therneau, T, Grambsch, P 2000Modeling Survival Data: Extending the Cox Model.Springer-VerlagNew YorkGoogle Scholar
- Gore, S, Pocock, S, Kerr, G 1984Regression models and non-proportional hazards in the analysis of breast cancer survival.Appl Statist33176195Google Scholar
- Gasparini, G, Meli, S, Panizzoni, G, Visona, A, Boracchi, P, Bevilacqua, P, Marubini, E, Pozza, F 1991Peritumoral lymphatic vessel invasion compared with DNA ploidy, proliferative activity, and other pathologic features as prognostic indicators in operable breast cancerBreast, Cancer Res and Treat20195204Google Scholar
- Swanson, G, Lin, C 1994Survival patterns among younger women with breast cancer: the effects of age, race, stage, and treatmentJ Nat Cancer Inst Monogr166977Google Scholar
- Black, W, Welch, H 1997Screening for diseaseAm J Radiology168311Google Scholar