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Hormone receptor status and survival in a population‐based cohort of patients with breast carcinoma
Abstract
BACKGROUND: The objective of this study was to assess hormone receptor status as an independent predictor of survival in a population‐based cohort of women with breast carcinoma who were followed for up to 11 years. METHODS: Since 1990, the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) Program has collected data on hormone receptor status among patients with breast carcinoma. In a cohort of 205,736 women with breast carcinoma age ≥ 20 years at diagnosis who were entered into the SEER data base between 1990 and 2000, the authors analyzed the association of hormone receptor status with year of diagnosis, patient age, disease stage, tumor histology, tumor grade, race/ethnicity, and metropolitan/statewide residence areas. Kaplan–Meier survival curves were compared according to hormone receptor status, and Cox proportional‐hazards regression models were used to assess the association of hormone receptor status with breast carcinoma‐specific and all‐cause mortality controlling for age, disease stage, tumor grade, tumor histology, race/ethnicity, and SEER region. RESULTS: Women who had tumors that were positive for both estrogen and progesterone hormone receptors had significantly better survival than other women with breast carcinoma in the overall cohort, within each stage, and in the younger and older age groups, although the survival advantage was greater among women age ≤ 50 years than among older women. Hormone receptor status was associated with mortality even when patient age, disease stage, tumor grade, tumor histology, race/ethnicity, and metropolitan/statewide residence areas were taken into account. CONCLUSIONS: Hormone receptor status was identified as an independent predictor of outcome in women with breast carcinoma. Data from clinical trials with long follow‐up may shed light on whether and how the benefit of hormonal and other treatment varies with hormone receptor status. Cancer 2005. © 2005 American Cancer Society.
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Cites
Modeling Survival Data: Extending the Cox Model
Therneau, T. M., & Grambsch, P. M. (2000) · Statistics for Biology and Health · doi:10.1007/978-1-4757-3294-8 · Cited by 8,674
Asymptotically Efficient Rank Invariant Test Procedures
Peto, R., & Peto, J. (1972) · Journal of the Royal Statistical Society. Series A (General) · doi:10.2307/2344317 · Cited by 3,393
Time-dependence of hazard ratios for prognostic factors in primary breast cancer
Hilsenbeck, S. G., Ravdin, P. M., de Moor, C. A., Chamness, G. C., Osborne, C. K., & Clark, G. M. (1998) · Breast Cancer Research and Treatment · doi:10.1023/a:1006133418245 · Cited by 237
Cited by
Dunnwald, L. K., Rossing, M. A., & Li, C. I. (2007) · Breast Cancer Research · doi:10.1186/bcr1639 · Cited by 785
Prat, A., Cheang, M. C. U., Martín, M., Parker, J. S., Carrasco, E., Caballero, R., Tyldesley, S., Gelmon, K., Bernard, P. S., Nielsen, T. O., et al. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.43.4134 · Cited by 587
Prognostic versus predictive value of biomarkers in oncology
Oldenhuis, C. N. A. M., Oosting, S. F., Gietema, J. A., & de Vries, E. G. E. (2008) · European Journal of Cancer · doi:10.1016/j.ejca.2008.03.006 · Cited by 349
Metadata
- Authors
- Grann, V. R., Troxel, A. B., Zojwalla, N. J., Jacobson, J. S., Hershman, D., & Neugut, A. I.
- Venue
- Cancer
- Publisher
- Wiley
- Published
- 2005-04-20
- Volume
- 103
- Issue
- 11
- Pages
- 2241-2251
- ISSN
- 0008-543X (ISSN-L)
- 1097-0142
- OpenAlex
- W1974026856
- Cited by
- 229
- References
- 3
- FWCI
- 3.20
- Type
- journal article
- Language
- en
- Open access
- closed
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