A complex systems model of breast cancer etiology: The Paradigm II Model.


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2023
Historique:
received: 15 01 2021
accepted: 24 02 2023
medline: 22 5 2023
pubmed: 19 5 2023
entrez: 19 5 2023
Statut: epublish

Résumé

Complex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers. We developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures. The Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.

Sections du résumé

BACKGROUND
Complex systems models of breast cancer have previously focused on prediction of prognosis and clinical events for individual women. There is a need for understanding breast cancer at the population level for public health decision-making, for identifying gaps in epidemiologic knowledge and for the education of the public as to the complexity of this most common of cancers.
METHODS AND FINDINGS
We developed an agent-based model of breast cancer for the women of the state of California using data from the U.S. Census, the California Health Interview Survey, the California Cancer Registry, the National Health and Nutrition Examination Survey and the literature. The model was implemented in the Julia programming language and R computing environment. The Paradigm II model development followed a transdisciplinary process with expertise from multiple relevant disciplinary experts from genetics to epidemiology and sociology with the goal of exploring both upstream determinants at the population level and pathophysiologic etiologic factors at the biologic level. The resulting model reproduces in a reasonable manner the overall age-specific incidence curve for the years 2008-2012 and incidence and relative risks due to specific risk factors such as BRCA1, polygenic risk, alcohol consumption, hormone therapy, breastfeeding, oral contraceptive use and scenarios for environmental toxin exposures.
CONCLUSIONS
The Paradigm II model illustrates the role of multiple etiologic factors in breast cancer from domains of biology, behavior and the environment. The value of the model is in providing a virtual laboratory to evaluate a wide range of potential interventions into the social, environmental and behavioral determinants of breast cancer at the population level.

Identifiants

pubmed: 37205649
doi: 10.1371/journal.pone.0282878
pii: PONE-D-21-01507
pmc: PMC10198497
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0282878

Informations de copyright

Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Déclaration de conflit d'intérêts

No authors have competing interests.

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Auteurs

Robert A Hiatt (RA)

Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.
Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, United States of America.

Lee Worden (L)

Francis I. Proctor Foundation for Research in Ophthalmology, University of California San Francisco, San Francisco, California, United States of America.

David Rehkopf (D)

Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, United States of America.

Natalie Engmann (N)

Genentech, Inc. South San Francisco, San Francisco, California, United States of America.

Melissa Troester (M)

Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America.

John S Witte (JS)

Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, United States of America.

Kaya Balke (K)

Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California, United States of America.

Christian Jackson (C)

Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California, United States of America.

Janice Barlow (J)

Zero Breast Cancer (retired), San Rafael, California, United States of America.

Suzanne E Fenton (SE)

Division of the National Toxicology Program, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, North Carolina, United States of America.

Sarah Gehlert (S)

Suzanne Dworak-Peck School, University of Southern California, Los Angeles, United States of America.

Ross A Hammond (RA)

Brown School, Washington University, St Louis, Missouri, United States of America.

George Kaplan (G)

University of Michigan (retired), Ann Arbor, Michigan, United States of America.

John Kornak (J)

Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.

Krisida Nishioka (K)

School of Law, University of California, Berkeley, Berkeley, California, United States of America.

Thomas McKone (T)

School of Public Health, University of California, Berkeley, (Emeritus), Berkeley, California, United States of America.

Martyn T Smith (MT)

Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, California, United States of America.

Leonardo Trasande (L)

Department of Pediatrics, NYU Grossman School of Medicine, New York City, New York, United States of America.

Travis C Porco (TC)

Department of Epidemiology and Biostatistics, School of Medicine, University of California San Francisco, San Francisco, California, United States of America.
Francis I. Proctor Foundation for Research in Ophthalmology, University of California San Francisco, San Francisco, California, United States of America.

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