A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model

Cancer Epidemiol Biomarkers Prev. 2020 Sep;29(9):1720-1730. doi: 10.1158/1055-9965.EPI-20-0016. Epub 2020 Jul 8.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / etiology*
  • Breast Neoplasms / pathology
  • Female
  • Humans
  • Models, Theoretical