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Cancer Epidemiol Biomarkers Prev. 2014 Oct;23(10):2078-92. doi: 10.1158/1055-9965.EPI-14-0403. Epub 2014 Jul 13.

A multilevel model of postmenopausal breast cancer incidence.

Author information

1
Department of Epidemiology and Biostatistics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California. rhiatt@epi.ucsf.edu.
2
Department of Epidemiology and Biostatistics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California. Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California.
3
Francis I. Proctor Foundation, University of California San Francisco, San Francisco, California.
4
Department of Epidemiology and Biostatistics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
5
Department of Biochemistry and Biophysics, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
6
Zero Breast Cancer, San Rafael, California.
7
Department of Epidemiology, University of Michigan, Ann Arbor, Michigan.
8
Division of Research, Kaiser Permanente, Oakland, California.
9
Department of Medicine, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
10
Department of Anatomy, Helen Diller Family Comprehensive Cancer Center, University of California San Francisco, San Francisco, California.
11
Division of Environmental and Occupational Disease Control, California Department of Public Health, Richmond, California.
12
Department of Medicine, Stanford University, Stanford, California.

Abstract

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.

PMID:
25017248
DOI:
10.1158/1055-9965.EPI-14-0403
[Indexed for MEDLINE]
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