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JAMA Oncol. 2016 Oct 1;2(10):1295-1302. doi: 10.1001/jamaoncol.2016.1025.

Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States.

Author information

1
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.
2
Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
3
Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
4
Fred Hutchinson Cancer Research Center, Seattle, Washington5School of Public Health, University of Wisconsin-Milwaukee, Milwaukee.
5
Epidemiology Research Program, American Cancer Society, Atlanta Georgia.
6
Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia8Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia.
7
Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles.
8
Division of Cancer Prevention, National Cancer Institute, Bethesda, Maryland.
9
INSERM U1052 - Cancer Research Center of Lyon, Centre Léon Bérard, Lyon, France12Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, England.
10
Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst14Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
11
Lombardi Comprehensive Cancer Center, Georgetown University, Washington, DC.
12
Epidemiology Program, Cancer Research Center, University of Hawaii, Honolulu.
13
University of Hawaii Cancer Center, Honolulu.
14
Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
15
Department of Public Health, Aarhus University, Aarhus, Denmark.
16
Nutrition and Metabolism Section, International Agency for Research on Cancer, Lyon, France.
17
Escuela Andaluza de Salud Pública. Instituto de Investigación Biosanitaria ibs.GRANADA. Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain22CIBER de Epidemiología y Salud Pública (CIBERESP), Spain.
18
Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Australia.
19
Cancer Registry and Histopathology Unit, "Civic- M.P.Arezzo" Hospital, ASP Ragusa, Italy.
20
Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, Massachusetts26Department of Biostatistics, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
21
Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, Massachusetts.
22
German Cancer Research Center (DKFZ), Heidelberg, Germany.
23
Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia8Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia29Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
24
Fred Hutchinson Cancer Research Center, Seattle, Washington30University of Washington, School of Public Health and Community Medicine, Seattle.
25
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland31Breakthrough Breast Cancer Research Centre, Division of Genetics and Epidemiology, The Institute of Cancer Research, London, England.
26
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland32Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland33Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, Maryland.

Erratum in

Abstract

Importance:

An improved model for risk stratification can be useful for guiding public health strategies of breast cancer prevention.

Objective:

To evaluate combined risk stratification utility of common low penetrant single nucleotide polymorphisms (SNPs) and epidemiologic risk factors.

Design, Setting, and Participants:

Using a total of 17 171 cases and 19 862 controls sampled from the Breast and Prostate Cancer Cohort Consortium (BPC3) and 5879 women participating in the 2010 National Health Interview Survey, a model for predicting absolute risk of breast cancer was developed combining information on individual level data on epidemiologic risk factors and 24 genotyped SNPs from prospective cohort studies, published estimate of odds ratios for 68 additional SNPs, population incidence rate from the National Cancer Institute-Surveillance, Epidemiology, and End Results Program cancer registry and data on risk factor distribution from nationally representative health survey. The model is used to project the distribution of absolute risk for the population of white women in the United States after adjustment for competing cause of mortality.

Exposures:

Single nucleotide polymorphisms, family history, anthropometric factors, menstrual and/or reproductive factors, and lifestyle factors.

Main Outcomes and Measures:

Degree of stratification of absolute risk owing to nonmodifiable (SNPs, family history, height, and some components of menstrual and/or reproductive history) and modifiable factors (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared], menopausal hormone therapy [MHT], alcohol, and smoking).

Results:

The average absolute risk for a 30-year-old white woman in the United States developing invasive breast cancer by age 80 years is 11.3%. A model that includes all risk factors provided a range of average absolute risk from 4.4% to 23.5% for women in the bottom and top deciles of the risk distribution, respectively. For women who were at the lowest and highest deciles of nonmodifiable risks, the 5th and 95th percentile range of the risk distribution associated with 4 modifiable factors was 2.9% to 5.0% and 15.5% to 25.0%, respectively. For women in the highest decile of risk owing to nonmodifiable factors, those who had low BMI, did not drink or smoke, and did not use MHT had risks comparable to an average woman in the general population.

Conclusions and Relevance:

This model for absolute risk of breast cancer including SNPs can provide stratification for the population of white women in the United States. The model can also identify subsets of the population at an elevated risk that would benefit most from risk-reduction strategies based on altering modifiable factors. The effectiveness of this model for individual risk communication needs further investigation.

PMID:
27228256
PMCID:
PMC5719876
DOI:
10.1001/jamaoncol.2016.1025
[Indexed for MEDLINE]
Free PMC Article

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