US Incidence of Breast Cancer Subtypes Defined by Joint Hormone Receptor and HER2 Status

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ID: 295022
2014
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Abstract
In 2010, Surveillance, Epidemiology, and End Results (SEER) registries began collecting human epidermal growth factor 2 (HER2) receptor status for breast cancer cases. Breast cancer subtypes defined by joint hormone receptor (HR; estrogen receptor [ER] and progesterone receptor [PR]) and HER2 status were assessed across the 28% of the US population that is covered by SEER registries. Age-specific incidence rates by subtype were calculated for non-Hispanic (NH) white, NH black, NH Asian Pacific Islander (API), and Hispanic women. Joint HR/HER2 status distributions by age, race/ethnicity, county-level poverty, registry, stage, Bloom–Richardson grade, tumor size, and nodal status were evaluated using multivariable adjusted polytomous logistic regression. All statistical tests were two-sided. Among case patients with known HR/HER2 status, 36810 (72.7%) were found to be HR+/HER2−, 6193 (12.2%) were triple-negative (HR−/HER2−), 5240 (10.3%) were HR+/HER2+, and 2328 (4.6%) were HR−/HER2+; 6912 (12%) had unknown HR/HER2 status. NH white women had the highest incidence rate of the HR+/HER2− subtype, and NH black women had the highest rate of the triple-negative subtype. Compared with women with the HR+/HER2− subtype, triple-negative patients were more likely to be NH black and Hispanic; HR+/HER2+ patients were more likely to be NH API; and HR−/HER2+ patients were more likely to be NH black, NH API, and Hispanic. Patients with triple-negative, HR+/HER2+, and HR−/HER2+ breast cancer were 10% to 30% less likely to be diagnosed at older ages compared with HR+/HER2− patients and 6.4-fold to 20.0-fold more likely to present with high-grade disease. In the future, SEER data can be used to monitor clinical outcomes in women diagnosed with different molecular subtypes of breast cancer for a large portion (approximately 28%) of the US population.
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openalex_W2159427817 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Nadia Howlader, Sean F. Altekruse, Christopher I. Li, Vivien W. Chen, Christina A. Clarke, Lynn A. G. Ries, Kathleen A. Cronin
Journal JNCI Journal of the National Cancer Institute
Year 2014
DOI
10.1093/jnci/dju055
URL
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