Evidence map›Paper›PMID 41546752›Full record

ArticleCancer causes & control : CCC2026

Persistent poverty and breast cancer incidence by tumor subtype: intersections of rural/urban residence and race within USA Surveillance Epidemiology and End Results Registries, 2017 to 2021.

Heather R Sherr, Amr S Soliman, Kimberly A Bertrand, Kelly A Hirko

Abstract read
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Article in Cancer causes & control : CCC, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Heather R SherrWashington University School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0009-0008-2364-3689
Amr S SolimanCity University of New York Medical School, New York, NY, USA.ORCID http://orcid.org/0000-0003-2284-360X
Kimberly A BertrandSlone Epidemiology Center at Boston University, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4565-7618
Kelly A HirkoDepartment of Epidemiology & Biostatistics, College of Human Medicine, Michigan State University, East Lansing, MI, USA. hirkokel@msu.edu.ORCID http://orcid.org/0000-0002-0050-655X

Funding

Cancer Epidemiology Education in Special Populations Program-15R25CA112383 · NCI · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI Amr Soliman · 2006 to 2026
$6.1M
NCI NIH HHS CA112383NCI NIH HHS R25 CA112383
6 · The paper itself

Abstract

purposeBreast cancer characteristics and outcomes vary by tumor subtype, poverty, race, and geography. Persistent poverty (> 20% residents in poverty for 30+ years) has been associated with breast cancer risk, but whether associations differ by subtype is unknown. We examined subtype-specific breast cancer incidence by persistent poverty, stratified by rurality and race.

methodsUsing county-level Surveillance, Epidemiology, and End Results data from 2017 to 2021 (excluding 2020), we calculated Luminal A, Luminal B, HER2-enriched, and triple-negative breast cancer (TNBC) incidence rates. We estimated rate differences (RDs) by persistent poverty using age-adjusted and multivariable linear regression models, with stratification by rurality and county racial composition.

resultsIn age-adjusted models, persistent poverty counties had lower incidence of Luminal A (RD - 13.58, 95% CI = - 19.8, - 7.4) and higher TNBC (RD = 3.82, 95% CI = 2.0, 5.6) compared to non-persistently poor counties. Differences were not significant in multivariable models. In stratified analysis, higher TNBC rates were observed in persistently poor rural (multivariable RD =1.70, 95% CI = 0.3, 4.8) but not urban (multivariable RD = - 1.07, 95% CI = - 4.7, 2.5; p

conclusionResults from this study suggest that differences in breast cancer subtypes by persistent poverty status are largely explained by other measures of more recent disadvantage including recent poverty, unemployment, uninsurance, and race. Targeted strategies are needed to address breast cancer disparities within socioeconomically disadvantaged communities.

Indexed as

Breast NeoplasmsPovertyRural PopulationUrban PopulationAdultAgedFemaleHumansIncidenceMiddle AgedRacial GroupsRegistriesSEER ProgramUnited StatesBreast cancerPersistent povertyRuralSubtypes

Identifiers

PMID41546752
PMCPMC12812092

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.