Health and Racial Disparity in Breast Cancer
Open accessAbstract
Breast cancer is the most common noncutaneous malignancy and the second most lethal form of cancer among women in the United States. It currently affects more than one in ten women worldwide. The chance for a female to be diagnosed with breast cancer during her lifetime has significantly increased from 1 in 11 women in 1975 to 1 in 8 women (Altekruse, SEER Cancer Statistics Review, 1975-2007. National Cancer Institute, Bethesda, 2010). This chance for a female of being diagnosed with cancer generally increases with age (Howlader et al, SEER Cancer Statistics Review, 1975-2010. National Cancer Institute, Bethesda, 2013). Fortunately, the mortality rate from breast cancer has decreased in recent years due to increased emphasis on early detection and more effective treatments in the White population. Although the mortality rates have declined in some ethnic populations, the overall cancer incidence among African American and Hispanic population has continued to grow. The goal of the work presented in this book chapter is to highlight similarities and differences in breast cancer morbidity and mortality rates among non-Hispanic white and non-Hispanic black populations. This book chapter also provides an overview of breast cancer, racial/ethnic disparities in breast cancer, breast cancer incidence and mortality rate linked to hereditary, major risk factors of breast cancer among minority population, breast cancer treatment, and health disparity. A considerable amount of breast cancer treatment research have been conducted, but with limited success for African Americans compared to other ethnic groups. Therefore, new strategies and approaches are needed to promote breast cancer prevention, improve survival rates, reduce breast cancer mortality, and ultimately improve the health outcomes of racial/ethnic minorities. In addition, it is vital that leaders and medical professionals from minority population groups be represented in decision-making in research so that racial disparity in breast cancer can be well-studied, fully addressed, and ultimately eliminated in breast cancer.
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Healthcare AI systems have the potential to foster access to healthcare for underserved populations, while improving care quality at both the individual patient and population levels, at reduced cost for patients, payors, and society.
“Healthcare AI systems have the potential to foster access to healthcare for underserved populations, while improving care quality at both the level of the individual patient and the population, at reduced cost for patients, payors, and society2–8,10,12–16.”
From Considerations for addressing bias in artificial intelligence for health equity (2023) · cites this paper as [5]
Lack of equitable access to diagnosis and treatment is prominent in diseases ranging from breast cancer, depression, to diabetic eye disease.
“While there are multiple reasons for avoidable health inequities2, lack of equitable access to diagnosis and treatment are prominent in diseases ranging from breast cancer, depression, to diabetic eye disease3–8.”
From Considerations for addressing bias in artificial intelligence for health equity (2023) · cites this paper as [5]
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Considerations for addressing bias in artificial intelligence for health equity
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- Authors
- Yedjou, C. G., Sims, J. N., Miele, L., Noubissi, F., Lowe, L., Fonseca, D. D., Alo, R. A., Payton, M., & Tchounwou, P. B.
- Affiliations
- Jackson Medical Mall Thad Cochran Center (US)
- Louisiana State University Health Sciences Center New Orleans (US)
- Jackson State University (US)
- Venue
- Advances in Experimental Medicine and Biology
- Publisher
- Springer International Publishing
- Published
- 2019
- Volume
- 1152
- Pages
- 31-49
- ISSN
- 0065-2598 (ISSN-L)
- 2214-8019
- PMC
- PMC6941147
- OpenAlex
- W2971201970
- Cited by
- 509
- References
- 135
- Citations by year
- 2026: 35 · 2025: 85 · 2024: 107 · 2023: 121 · 2022: 84 · 2021: 57 · 2020: 18 · 2019: 1
- FWCI
- 59.51
- Type
- book chapter
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Advances in experimental medicine and biology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of General Medical Sciences (U54GM104940)
- National Institute on Minority Health and Health Disparities (G12MD007581, P20MD006899)
- Topics
- Health Sciences › Medicine › Oncology › Global Cancer Incidence and Screening
- Health Sciences › Medicine › Oncology › Cancer Risks and Factors
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- breast cancer, racial disparities, health disparities, African American women, non-Hispanic white women, breast cancer incidence, breast cancer mortality, breast cancer risk factors, hereditary breast cancer, breast cancer treatment, minority groups, breast cancer prevention, underrepresentation in research
- MeSH terms
- Black or African American, Breast Neoplasms, Female, Humans, United States, White People, Health Status Disparities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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