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Population simulation modeling of disparities in US breast cancer mortality.
Mandelblatt, Jeanne S; Schechter, Clyde B; Stout, Natasha K; Huang, Hui; Stein, Sarah; Hunter Chapman, Christina; Trentham-Dietz, Amy; Jayasekera, Jinani; Gangnon, Ronald E; Hampton, John M; Abraham, Linn; O'Meara, Ellen S; Sheppard, Vanessa B; Lee, Sandra J.
Afiliación
  • Mandelblatt JS; Department of Oncology, Georgetown University Medical Center and Cancer Prevention and Control Program at Georgetown Lombardi Comprehensive Cancer Center, Washington, DC, USA.
  • Schechter CB; Departments of Family and Social Medicine and of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
  • Stout NK; Department of Population Sciences, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
  • Huang H; Department of Data Science, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
  • Stein S; Department of Population Sciences, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA.
  • Hunter Chapman C; Department of Radiation Oncology, Section of Health Services Research, Baylor College of Medicine and Health Policy, Quality and Informatics Program at the Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA.
  • Trentham-Dietz A; Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.
  • Jayasekera J; Health Equity and Decision Sciences Research Lab, National Institute on Minority Health and Health Disparities, Intramural Research Program, National Institutes of Health, Bethesda, MD, USA.
  • Gangnon RE; Departments of Population Health Sciences and of Biostatistics and Medical Informatics and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.
  • Hampton JM; Department of Population Health Sciences and Carbone Cancer Center, University of Wisconsin-Madison, Madison, WI, USA.
  • Abraham L; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
  • O'Meara ES; Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA.
  • Sheppard VB; Department of Health Behavior and Policy and Massey Cancer Center, Virginia Commonwealth University, Richmond, VA, USA.
  • Lee SJ; Department of Data Science, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA.
J Natl Cancer Inst Monogr ; 2023(62): 178-187, 2023 11 08.
Article en En | MEDLINE | ID: mdl-37947337
ABSTRACT

BACKGROUND:

Populations of African American or Black women have persistently higher breast cancer mortality than the overall US population, despite having slightly lower age-adjusted incidence.

METHODS:

Three 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.

RESULTS:

Results 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.

CONCLUSION:

Our 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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 / 2_ODS3 Problema de salud: 1_acesso_equitativo_servicos / 2_cobertura_universal Asunto principal: Neoplasias de la Mama / Disparidades en el Estado de Salud Límite: Female / Humans País/Región como asunto: America do norte Idioma: En Revista: J Natl Cancer Inst Monogr Asunto de la revista: NEOPLASIAS Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Contexto en salud: 1_ASSA2030 / 2_ODS3 Problema de salud: 1_acesso_equitativo_servicos / 2_cobertura_universal Asunto principal: Neoplasias de la Mama / Disparidades en el Estado de Salud Límite: Female / Humans País/Región como asunto: America do norte Idioma: En Revista: J Natl Cancer Inst Monogr Asunto de la revista: NEOPLASIAS Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos
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