Article

Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model

Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California 94143-1732, USA.
Annals of internal medicine (Impact Factor: 16.1). 04/2008; 148(5):337-47. DOI: 10.7326/0003-4819-148-5-200803040-00004
Source: PubMed

ABSTRACT Current models for assessing breast cancer risk are complex and do not include breast density, a strong risk factor for breast cancer that is routinely reported with mammography.
To develop and validate an easy-to-use breast cancer risk prediction model that includes breast density.
Empirical model based on Surveillance, Epidemiology, and End Results incidence, and relative hazards from a prospective cohort.
Screening mammography sites participating in the Breast Cancer Surveillance Consortium.
1,095,484 women undergoing mammography who had no previous diagnosis of breast cancer.
Self-reported age, race or ethnicity, family history of breast cancer, and history of breast biopsy. Community radiologists rated breast density by using 4 Breast Imaging Reporting and Data System categories.
During 5.3 years of follow-up, invasive breast cancer was diagnosed in 14,766 women. The breast density model was well calibrated overall (expected-observed ratio, 1.03 [95% CI, 0.99 to 1.06]) and in racial and ethnic subgroups. It had modest discriminatory accuracy (concordance index, 0.66 [CI, 0.65 to 0.67]). Women with low-density mammograms had 5-year risks less than 1.67% unless they had a family history of breast cancer and were older than age 65 years.
The model has only modest ability to discriminate between women who will develop breast cancer and those who will not.
A breast cancer prediction model that incorporates routinely reported measures of breast density can estimate 5-year risk for invasive breast cancer. Its accuracy needs to be further evaluated in independent populations before it can be recommended for clinical use.

Download full-text

Full-text

Available from: William E Barlow, Aug 19, 2015
0 Followers
 · 
105 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Breast cancer is one of the most common cancers among women and the leading cause of death in women between the ages of 45-60 in most developed countries. The effi cacy of prevention options has been established and includes lifestyle modifi cations, chemopreven-tion, and prophylactic surgery. Despite the effi -cacy of these options, breast cancer prevention remains underused, resulting in avoidable mor-bidity and mortality. Here, the main barriers to effective use of breast cancer prevention are outlined and a framework to facilitate patient-centered and evidence-based breast cancer prevention decision making is presented. The framework is intended to encourage a shared decision making approach to prevention deci-sions, within the context of a woman's overall health. The inclusion of effective lifestyle in-terventions makes this framework relevant to most women, and is not exclusive to women at increased risk of developing breast cancer.
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Mammographic density is a strong, independent risk factor for breast cancer. Women with high mammographic density have a fourfold increased risk for breast cancer compared with women with low density. Because age and obesity are the strongest predictors of mammographic density, it is important to adjust for them in risk analyses. In randomized trials, tamoxifen decreased risk for breast cancer and also decreased mammographic density. Combined estrogen plus progestin therapy increased mammographic density. Density is a strong risk factor in low-risk groups (Asian women) and high-risk groups (BRCA mutation carriers). Several risk assessment tools now incorporate mammographic density, including an updated Gail model, though these models require additional validation before they should be used widely. Improvements in density measurements may allow risk assessment to occur routinely with mammography and improve targeting of breast cancer prevention efforts.
    Current Breast Cancer Reports 09/2009; 1(3):175-180. DOI:10.1007/s12609-009-0025-1
  • Source
Show more