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

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.

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

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.

A multilevel model of postmenopausal breast cancer incidence.

BACKGROUND: Breast cancer has a complex etiology that includes genetic, biologic, behavioral, environmental, and social factors. Etiologic factors are frequently studied in isolation with adjustment for confounding, mediating, and moderating effects of other factors. A complex systems model approach may present a more comprehensive picture of the multifactorial etiology of breast cancer. METHODS: We took a transdisciplinary approach with experts from relevant fields to develop a conceptual model of the etiology of postmenopausal breast cancer. The model incorporated evidence of both the strength of association and the quality of the evidence. We operationalized this conceptual model through a mathematical simulation model with a subset of variables, namely, age, race/ethnicity, age at menarche, age at first birth, age at menopause, obesity, alcohol consumption, income, tobacco use, use of hormone therapy (HT), and BRCA1/2 genotype. RESULTS: In simulating incidence for California in 2000, the separate impact of individual variables was modest, but reduction in HT, increase in the age at menarche, and to a lesser extent reduction in excess BMI >30 kg/m(2) were more substantial. CONCLUSIONS: Complex systems models can yield new insights on the etiologic factors involved in postmenopausal breast cancer. Modification of factors at a population level may only modestly affect risk estimates, while still having an important impact on the absolute number of women affected. IMPACT: This novel effort highlighted the complexity of breast cancer etiology, revealed areas of challenge in the methodology of developing complex systems models, and suggested additional areas for further study.