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Racial disparities in triple negative breast cancer: toward a causal architecture approach

BACKGROUND: Triple negative breast cancer (TNBC) is an aggressive subtype of invasive breast cancer that disproportionately affects Black women and contributes to racial disparities in breast cancer mortality. Prior research has suggested that neighborhood effects may contribute to this disparity be...

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Autores principales: Siegel, Scott D., Brooks, Madeline M., Lynch, Shannon M., Sims-Mourtada, Jennifer, Schug, Zachary T., Curriero, Frank C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9158353/
https://www.ncbi.nlm.nih.gov/pubmed/35650633
http://dx.doi.org/10.1186/s13058-022-01533-z
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author Siegel, Scott D.
Brooks, Madeline M.
Lynch, Shannon M.
Sims-Mourtada, Jennifer
Schug, Zachary T.
Curriero, Frank C.
author_facet Siegel, Scott D.
Brooks, Madeline M.
Lynch, Shannon M.
Sims-Mourtada, Jennifer
Schug, Zachary T.
Curriero, Frank C.
author_sort Siegel, Scott D.
collection PubMed
description BACKGROUND: Triple negative breast cancer (TNBC) is an aggressive subtype of invasive breast cancer that disproportionately affects Black women and contributes to racial disparities in breast cancer mortality. Prior research has suggested that neighborhood effects may contribute to this disparity beyond individual risk factors. METHODS: The sample included a cohort of 3316 breast cancer cases diagnosed between 2012 and 2020 in New Castle County, Delaware, a geographic region of the US with elevated rates of TNBC. Multilevel methods and geospatial mapping evaluated whether the race, income, and race/income versions of the neighborhood Index of Concentration at the Extremes (ICE) metric could efficiently identify census tracts (CT) with higher odds of TNBC relative to other forms of invasive breast cancer. Odds ratios (OR) and 95% confidence intervals (CI) were reported; p-values < 0.05 were significant. Additional analyses examined area-level differences in exposure to metabolic risk factors, including unhealthy alcohol use and obesity. RESULTS: The ICE-Race, -Income-, and Race/Income metrics were each associated with greater census tract odds of TNBC on a bivariate basis. However, only ICE-Race was significantly associated with higher odds of TNBC after adjustment for patient-level age and race (most disadvantaged CT: OR = 2.09; 95% CI 1.40–3.13), providing support for neighborhood effects. Higher counts of alcohol and fast-food retailers, and correspondingly higher rates of unhealthy alcohol use and obesity, were observed in CTs that were classified into the most disadvantaged ICE-Race quintile and had the highest odds of TNBC. CONCLUSION: The use of ICE can facilitate the monitoring of cancer inequities and advance the study of racial disparities in breast cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-022-01533-z.
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spelling pubmed-91583532022-06-02 Racial disparities in triple negative breast cancer: toward a causal architecture approach Siegel, Scott D. Brooks, Madeline M. Lynch, Shannon M. Sims-Mourtada, Jennifer Schug, Zachary T. Curriero, Frank C. Breast Cancer Res Research BACKGROUND: Triple negative breast cancer (TNBC) is an aggressive subtype of invasive breast cancer that disproportionately affects Black women and contributes to racial disparities in breast cancer mortality. Prior research has suggested that neighborhood effects may contribute to this disparity beyond individual risk factors. METHODS: The sample included a cohort of 3316 breast cancer cases diagnosed between 2012 and 2020 in New Castle County, Delaware, a geographic region of the US with elevated rates of TNBC. Multilevel methods and geospatial mapping evaluated whether the race, income, and race/income versions of the neighborhood Index of Concentration at the Extremes (ICE) metric could efficiently identify census tracts (CT) with higher odds of TNBC relative to other forms of invasive breast cancer. Odds ratios (OR) and 95% confidence intervals (CI) were reported; p-values < 0.05 were significant. Additional analyses examined area-level differences in exposure to metabolic risk factors, including unhealthy alcohol use and obesity. RESULTS: The ICE-Race, -Income-, and Race/Income metrics were each associated with greater census tract odds of TNBC on a bivariate basis. However, only ICE-Race was significantly associated with higher odds of TNBC after adjustment for patient-level age and race (most disadvantaged CT: OR = 2.09; 95% CI 1.40–3.13), providing support for neighborhood effects. Higher counts of alcohol and fast-food retailers, and correspondingly higher rates of unhealthy alcohol use and obesity, were observed in CTs that were classified into the most disadvantaged ICE-Race quintile and had the highest odds of TNBC. CONCLUSION: The use of ICE can facilitate the monitoring of cancer inequities and advance the study of racial disparities in breast cancer. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13058-022-01533-z. BioMed Central 2022-06-01 2022 /pmc/articles/PMC9158353/ /pubmed/35650633 http://dx.doi.org/10.1186/s13058-022-01533-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Siegel, Scott D.
Brooks, Madeline M.
Lynch, Shannon M.
Sims-Mourtada, Jennifer
Schug, Zachary T.
Curriero, Frank C.
Racial disparities in triple negative breast cancer: toward a causal architecture approach
title Racial disparities in triple negative breast cancer: toward a causal architecture approach
title_full Racial disparities in triple negative breast cancer: toward a causal architecture approach
title_fullStr Racial disparities in triple negative breast cancer: toward a causal architecture approach
title_full_unstemmed Racial disparities in triple negative breast cancer: toward a causal architecture approach
title_short Racial disparities in triple negative breast cancer: toward a causal architecture approach
title_sort racial disparities in triple negative breast cancer: toward a causal architecture approach
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9158353/
https://www.ncbi.nlm.nih.gov/pubmed/35650633
http://dx.doi.org/10.1186/s13058-022-01533-z
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