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Cancer Epidemiology, Biomarkers & Prevention
Cancer Epidemiology, Biomarkers & Prevention
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A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model

Robert A. Hiatt, Natalie J. Engmann, Kaya Balke and David H. Rehkopf; for the Paradigm II Multidisciplinary Panel
Robert A. Hiatt
1Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, California.
2Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
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  • ORCID record for Robert A. Hiatt
  • For correspondence: Robert.Hiatt@ucsf.edu
Natalie J. Engmann
3Genentech, Inc., South San Francisco, California.
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Kaya Balke
2Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
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David H. Rehkopf
4Department of Medicine, Stanford University, Palo Alto, California.
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DOI: 10.1158/1055-9965.EPI-20-0016 Published September 2020
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Abstract

Background: The etiology of breast cancer is a complex system of interacting factors from multiple domains. New knowledge about breast cancer etiology continues to be produced by the research community, and the communication of this knowledge to other researchers, practitioners, decision makers, and the public is a challenge.

Methods: We updated the previously published Paradigm model (PMID: 25017248) to create a framework that describes breast cancer etiology in four overlapping domains of biologic, behavioral, environmental, and social determinants. This new Paradigm II conceptual model was part of a larger modeling effort that included input from multiple experts in fields from genetics to sociology, taking a team and transdisciplinary approach to the common problem of describing breast cancer etiology for the population of California women in 2010. Recent literature was reviewed with an emphasis on systematic reviews when available and larger epidemiologic studies when they were not. Environmental chemicals with strong animal data on etiology were also included.

Results: The resulting model illustrates factors with their strength of association and the quality of the available data. The published evidence supporting each relationship is made available herein, and also in an online dynamic model that allows for manipulation of individual factors leading to breast cancer (https://cbcrp.org/causes/).

Conclusions: The Paradigm II model illustrates known etiologic factors in breast cancer, as well as gaps in knowledge and areas where better quality data are needed.

Impact: The Paradigm II model can be a stimulus for further research and for better understanding of breast cancer etiology.

Footnotes

  • Cancer Epidemiol Biomarkers Prev 2020;29:1720–30

  • Received January 6, 2020.
  • Revision received March 9, 2020.
  • Accepted June 4, 2020.
  • Published first July 8, 2020.
  • ©2020 American Association for Cancer Research.
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Cancer Epidemiology Biomarkers & Prevention: 29 (9)
September 2020
Volume 29, Issue 9
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A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model
Robert A. Hiatt, Natalie J. Engmann, Kaya Balke and David H. Rehkopf for the Paradigm II Multidisciplinary Panel
Cancer Epidemiol Biomarkers Prev September 1 2020 (29) (9) 1720-1730; DOI: 10.1158/1055-9965.EPI-20-0016

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A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model
Robert A. Hiatt, Natalie J. Engmann, Kaya Balke and David H. Rehkopf for the Paradigm II Multidisciplinary Panel
Cancer Epidemiol Biomarkers Prev September 1 2020 (29) (9) 1720-1730; DOI: 10.1158/1055-9965.EPI-20-0016
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