Caroline Dickens1,2, Ruth M Pfeiffer3, William F Anderson3, Raquel Duarte4, Patricia Kellett5, Joachim Schüz6, Danuta Kielkowski5, Valerie A McCormack6. 1. Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France. caroline.dickens@wits.ac.za. 2. Department of Internal Medicine, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg, 2193, South Africa. caroline.dickens@wits.ac.za. 3. Division of Cancer Epidemiology and Genetics, National Cancer Institute, Biostatistics Branch, Executive Plaza South Rm 8036, 6120 Executive Blvd, Bethesda, MD, USA. 4. Department of Internal Medicine, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg, 2193, South Africa. 5. National Cancer Registry of South Africa, National Health and Laboratory Services, Johannesburg, South Africa. 6. Section of Environment and Radiation, International Agency for Research on Cancer, Lyon, France.
Abstract
PURPOSE: Bimodal age distributions at diagnosis have been widely observed among US and European female breast cancer populations. To determine whether bimodal breast cancer distributions are also present in a sub-Saharan African population, we investigated female breast cancer in South Africa. METHODS: Using the South African National Cancer Registry data, we examined age-at-diagnosis frequency distributions (density plots) for breast cancer overall and by their receptor (oestrogen, progesterone and HER2) determinants among black and white women diagnosed during 2009-2011 in the public healthcare sector. For comparison, we also analysed corresponding 2010-2011 US SEER data. We investigated density plots using flexible mixture models, allowing early/late-onset membership to depend on receptor status. RESULTS: We included 8857 women from South Africa, 7176 (81 %) with known oestrogen receptor status, and 95064 US women. Bimodality was present in all races, with an early-onset mode between ages 40-50 years and a late-onset mode among ages 60-70 years. The early-onset mode was younger in South African black women (age 38), compared to other groups (45-54 years). CONCLUSIONS: Consistent patterns of bimodality and of its receptor determinants were present across breast cancer patient populations in South Africa and the US. Although the clinical spectrum of breast cancer is well acknowledged as heterogeneous, universal early- and late-onset age distributions at diagnosis suggest that breast cancer etiology consists of a mixture two main types.
PURPOSE: Bimodal age distributions at diagnosis have been widely observed among US and European female breast cancer populations. To determine whether bimodal breast cancer distributions are also present in a sub-Saharan African population, we investigated female breast cancer in South Africa. METHODS: Using the South African National Cancer Registry data, we examined age-at-diagnosis frequency distributions (density plots) for breast cancer overall and by their receptor (oestrogen, progesterone and HER2) determinants among black and white women diagnosed during 2009-2011 in the public healthcare sector. For comparison, we also analysed corresponding 2010-2011 US SEER data. We investigated density plots using flexible mixture models, allowing early/late-onset membership to depend on receptor status. RESULTS: We included 8857 women from South Africa, 7176 (81 %) with known oestrogen receptor status, and 95064 US women. Bimodality was present in all races, with an early-onset mode between ages 40-50 years and a late-onset mode among ages 60-70 years. The early-onset mode was younger in South African black women (age 38), compared to other groups (45-54 years). CONCLUSIONS: Consistent patterns of bimodality and of its receptor determinants were present across breast cancerpatient populations in South Africa and the US. Although the clinical spectrum of breast cancer is well acknowledged as heterogeneous, universal early- and late-onset age distributions at diagnosis suggest that breast cancer etiology consists of a mixture two main types.
Entities:
Keywords:
Age distributions; Breast cancer; Receptors; South Africa
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