The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Breast cancer statistics, 2017, racial disparity in mortality by state
Open accessAbstract
In this article, the American Cancer Society provides an overview of female breast cancer statistics in the United States, including data on incidence, mortality, survival, and screening. Approximately 252,710 new cases of invasive breast cancer and 40,610 breast cancer deaths are expected to occur among US women in 2017. From 2005 to 2014, overall breast cancer incidence rates increased among Asian/Pacific Islander (1.7% per year), non‐Hispanic black (NHB) (0.4% per year), and Hispanic (0.3% per year) women but were stable in non‐Hispanic white (NHW) and American Indian/Alaska Native (AI/AN) women. The increasing trends were driven by increases in hormone receptor‐positive breast cancer, which increased among all racial/ethnic groups, whereas rates of hormone receptor‐negative breast cancers decreased. From 1989 to 2015, breast cancer death rates decreased by 39%, which translates to 322,600 averted breast cancer deaths in the United States. During 2006 to 2015, death rates decreased in all racial/ethnic groups, including AI/ANs. However, NHB women continued to have higher breast cancer death rates than NHW women, with rates 39% higher (mortality rate ratio [MRR], 1.39; 95% confidence interval [CI], 1.35‐1.43) in NHB women in 2015, although the disparity has ceased to widen since 2011. By state, excess death rates in black women ranged from 20% in Nevada (MRR, 1.20; 95% CI, 1.01‐1.42) to 66% in Louisiana (MRR, 1.66; 95% CI, 1.54, 1.79). Notably, breast cancer death rates were not significantly different in NHB and NHW women in 7 states, perhaps reflecting an elimination of disparities and/or a lack of statistical power. Improving access to care for all populations could eliminate the racial disparity in breast cancer mortality and accelerate the reduction in deaths from this malignancy nationwide. CA Cancer J Clin 2017;67:439‐448. © 2017 American Cancer Society.
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Writing Group for the Women's Health Initiative Investigators (2002) · JAMA: The Journal of the American Medical Association · doi:10.1001/jama.288.3.321 · Cited by 15,889
Siegel, R. L., Miller, K. D., & Jemal, A. (2017) · CA: A Cancer Journal for Clinicians · doi:10.3322/caac.21387 · Cited by 14,712
Self-citationEliminating racial disparities in colorectal cancer in the real world: It took a village
Grubbs, S. S., Polite, B. N., Carney, J., Bowser, W., Rogers, J., Katurakes, N., Hess, P., & Paskett, E. D. (2013) · Journal of Clinical Oncology · doi:10.1200/jco.2012.47.8412 · Cited by 201
Cited by
Harbeck, N., Penault-Llorca, F., Cortes, J., Gnant, M., Houssami, N., Poortmans, P., Ruddy, K., Tsang, J., & Cardoso, F. (2019) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0111-2 · Cited by 3,024
Epidemiological characteristics of and risk factors for breast cancer in the world
Momenimovahed, Z., & Salehiniya, H. (2019) · Breast Cancer: Targets and Therapy · doi:10.2147/bctt.s176070 · Cited by 1,050
Tripathy, D., Im, S.-A., Colleoni, M., Franke, F., Bardia, A., Harbeck, N., Hurvitz, S. A., Chow, L., Sohn, J., Lee, K. S., et al. (2018) · The Lancet Oncology · doi:10.1016/s1470-2045(18)30292-4 · Cited by 1,025
The pro-metastasis effect of circANKS1B in breast cancer
Zeng, K., He, B., Yang, B. B., Xu, T., Chen, X., Xu, M., Liu, X., Sun, H., Pan, Y., & Wang, S. (2018) · Molecular Cancer · doi:10.1186/s12943-018-0914-x · Cited by 319
Persistent post-mastectomy pain: risk factors and current approaches to treatment
Tait, R. C., Zoberi, K., Ferguson, M., Levenhagen, K., Luebbert, R. A., Rowland, K., Salsich, G. B., & Herndon, C. (2018) · The Journal of Pain · doi:10.1016/j.jpain.2018.06.002 · Cited by 190
Metadata
- Authors
- DeSantis, C. E., Ma, J., Goding Sauer, A., Newman, L. A., & Jemal, A.
- Venue
- CA: A Cancer Journal for Clinicians
- Publisher
- Wiley
- Published
- 2017-10-03
- Volume
- 67
- Issue
- 6
- Pages
- 439-448
- ISSN
- 0007-9235 (ISSN-L)
- 1542-4863
- OpenAlex
- W2762481118
- Cited by
- 1,879
- References
- 3
- FWCI
- 91.45
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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