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Modeling the effect of age in T1-2 breast cancer using the SEER database

BACKGROUND: Modeling the relationship between age and mortality for breast cancer patients may have important prognostic and therapeutic implications. METHODS: Data from 9 registries of the Surveillance, Epidemiology, and End Results Program (SEER) of the United States were used. This study employed...

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Autores principales: Tai, Patricia, Cserni, Gábor, Van De Steene, Jan, Vlastos, Georges, Voordeckers, Mia, Royce, Melanie, Lee, Sang-Joon, Vinh-Hung, Vincent, Storme, Guy
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2005
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1277821/
https://www.ncbi.nlm.nih.gov/pubmed/16212670
http://dx.doi.org/10.1186/1471-2407-5-130
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author Tai, Patricia
Cserni, Gábor
Van De Steene, Jan
Vlastos, Georges
Voordeckers, Mia
Royce, Melanie
Lee, Sang-Joon
Vinh-Hung, Vincent
Storme, Guy
author_facet Tai, Patricia
Cserni, Gábor
Van De Steene, Jan
Vlastos, Georges
Voordeckers, Mia
Royce, Melanie
Lee, Sang-Joon
Vinh-Hung, Vincent
Storme, Guy
author_sort Tai, Patricia
collection PubMed
description BACKGROUND: Modeling the relationship between age and mortality for breast cancer patients may have important prognostic and therapeutic implications. METHODS: Data from 9 registries of the Surveillance, Epidemiology, and End Results Program (SEER) of the United States were used. This study employed proportional hazards to model mortality in women with T1-2 breast cancers. The residuals of the model were used to examine the effect of age on mortality. This procedure was applied to node-negative (N0) and node-positive (N+) patients. All causes mortality and breast cancer specific mortality were evaluated. RESULTS: The relationship between age and mortality is biphasic. For both N0 and N+ patients among the T1-2 group, the analysis suggested two age components. One component is linear and corresponds to a natural increase of mortality with each year of age. The other component is quasi-quadratic and is centered around age 50. This component contributes to an increased risk of mortality as age increases beyond 50. It suggests a hormonally related process: the farther from menopause in either direction, the more prognosis is adversely influenced by the quasi-quadratic component. There is a complex relationship between hormone receptor status and other prognostic factors, like age. CONCLUSION: The present analysis confirms the findings of many epidemiological and clinical trials that the relationship between age and mortality is biphasic. Compared with older patients, young women experience an abnormally high risk of death. Among elderly patients, the risk of death from breast cancer does not decrease with increasing age. These facts are important in the discussion of options for adjuvant treatment with breast cancer patients.
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spelling pubmed-12778212005-11-05 Modeling the effect of age in T1-2 breast cancer using the SEER database Tai, Patricia Cserni, Gábor Van De Steene, Jan Vlastos, Georges Voordeckers, Mia Royce, Melanie Lee, Sang-Joon Vinh-Hung, Vincent Storme, Guy BMC Cancer Research Article BACKGROUND: Modeling the relationship between age and mortality for breast cancer patients may have important prognostic and therapeutic implications. METHODS: Data from 9 registries of the Surveillance, Epidemiology, and End Results Program (SEER) of the United States were used. This study employed proportional hazards to model mortality in women with T1-2 breast cancers. The residuals of the model were used to examine the effect of age on mortality. This procedure was applied to node-negative (N0) and node-positive (N+) patients. All causes mortality and breast cancer specific mortality were evaluated. RESULTS: The relationship between age and mortality is biphasic. For both N0 and N+ patients among the T1-2 group, the analysis suggested two age components. One component is linear and corresponds to a natural increase of mortality with each year of age. The other component is quasi-quadratic and is centered around age 50. This component contributes to an increased risk of mortality as age increases beyond 50. It suggests a hormonally related process: the farther from menopause in either direction, the more prognosis is adversely influenced by the quasi-quadratic component. There is a complex relationship between hormone receptor status and other prognostic factors, like age. CONCLUSION: The present analysis confirms the findings of many epidemiological and clinical trials that the relationship between age and mortality is biphasic. Compared with older patients, young women experience an abnormally high risk of death. Among elderly patients, the risk of death from breast cancer does not decrease with increasing age. These facts are important in the discussion of options for adjuvant treatment with breast cancer patients. BioMed Central 2005-10-08 /pmc/articles/PMC1277821/ /pubmed/16212670 http://dx.doi.org/10.1186/1471-2407-5-130 Text en Copyright © 2005 Tai et al; licensee BioMed Central Ltd.
spellingShingle Research Article
Tai, Patricia
Cserni, Gábor
Van De Steene, Jan
Vlastos, Georges
Voordeckers, Mia
Royce, Melanie
Lee, Sang-Joon
Vinh-Hung, Vincent
Storme, Guy
Modeling the effect of age in T1-2 breast cancer using the SEER database
title Modeling the effect of age in T1-2 breast cancer using the SEER database
title_full Modeling the effect of age in T1-2 breast cancer using the SEER database
title_fullStr Modeling the effect of age in T1-2 breast cancer using the SEER database
title_full_unstemmed Modeling the effect of age in T1-2 breast cancer using the SEER database
title_short Modeling the effect of age in T1-2 breast cancer using the SEER database
title_sort modeling the effect of age in t1-2 breast cancer using the seer database
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1277821/
https://www.ncbi.nlm.nih.gov/pubmed/16212670
http://dx.doi.org/10.1186/1471-2407-5-130
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