ArticleJournal of the National Cancer Institute. Monographs2023
Population simulation modeling of disparities in US breast cancer mortality.
Article in Journal of the National Cancer Institute. Monographs, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Breast cancer mortality by age and race and/or ethnicity across counties in the United States, 2000-2019.Journal of the National Cancer Institute · 2026Article
- Updates in Breast Cancer Screening and Diagnosis.Current treatment options in oncology · 2024Review
- Using simulation modeling to guide policy to reduce disparities and achieve equity in cancer outcomes: state of the science and a road map for the future.Journal of the National Cancer Institute. Monographs · 2023Article
- Data gaps and opportunities for modeling cancer health equity.Journal of the National Cancer Institute. Monographs · 2023Article
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Authors and funding
14 authors.
Funding
Abstract
backgroundPopulations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence.
methodsThree Cancer Intervention and Surveillance Modeling Network simulation teams modeled cancer mortality disparities between Black female populations and the overall US population. Model inputs used racial group-specific data from clinical trials, national registries, nationally representative surveys, and observational studies. Analyses began with cancer mortality in the overall population and sequentially replaced parameters for Black populations to quantify the percentage of modeled breast cancer morality disparities attributable to differences in demographics, incidence, access to screening and treatment, and variation in tumor biology and response to therapy.
resultsResults were similar across the 3 models. In 2019, racial differences in incidence and competing mortality accounted for a net ‒1% of mortality disparities, while tumor subtype and stage distributions accounted for a mean of 20% (range across models = 13%-24%), and screening accounted for a mean of 3% (range = 3%-4%) of the modeled mortality disparities. Treatment parameters accounted for the majority of modeled mortality disparities: mean = 17% (range = 16%-19%) for treatment initiation and mean = 61% (range = 57%-63%) for real-world effectiveness.
conclusionOur model results suggest that changes in policies that target improvements in treatment access could increase breast cancer equity. The findings also highlight that efforts must extend beyond policies targeting equity in treatment initiation to include high-quality treatment completion. This research will facilitate future modeling to test the effects of different specific policy changes on mortality disparities.
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