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

Maas P1, Barrdahl M2, Joshi AD3, Auer PL4, Gaudet MM5, Milne RL6, Schumacher FR7, Anderson WF1, Check D1, Chattopadhyay S1, Baglietto L6, Berg CD8, Chanock SJ1, Cox DG9, Figueroa JD1, Gail MH1, Graubard BI1, Haiman CA7, Hankinson SE10, Hoover RN1, Isaacs C11, Kolonel LN12, Le Marchand L13, Lee IM14, Lindström S3, Overvad K15, Romieu I16, Sanchez MJ17, Southey MC18, Stram DO7, Tumino R19, VanderWeele TJ20, Willett WC21, Zhang S14, Buring JE14, Canzian F22, Gapstur SM5, Henderson BE7, Hunter DJ3, Giles GG23, Prentice RL24, Ziegler RG1, Kraft P3, Garcia-Closas M25, Chatterjee N26.

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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.