Family history of breast cancer, breast density, and breast cancer risk in a U.S. breast cancer screening population

Thomas P. Ahern, Brian L. Sprague, Michael C.S. Bissell, Diana L Miglioretti, Diana S.M. Buist, Dejana Braithwaite, Karla Kerlikowske

Research output: Contribution to journalReview article

9 Scopus citations

Abstract

Background: The utility of incorporating detailed family history into breast cancer risk prediction hinges on its independent contribution to breast cancer risk. We evaluated associations between detailed family history and breast cancer risk while accounting for breast density. Methods: We followed 222,019 participants ages 35 to 74 in the Breast Cancer Surveillance Consortium, of whom 2,456 developed invasive breast cancer. We calculated standardized breast cancer risks within joint strata of breast density and simple (1st-degree female relative) or detailed (first-degree, seconddegree, or first-and second-degree female relative) breast cancer family history.Wefit log-binomial models to estimate age-specific breast cancer associations for simple and detailed family history, accounting for breast density. Results: Simple first-degree family history was associated with increased breast cancer risk compared with no first-degree history [Risk ratio (RR), 1.5; 95% confidence interval (CI), 1.0-2.1 at age 40; RR, 1.5; 95% CI, 1.3-1.7 at age 50; RR, 1.4; 95% CI, 1.2-1.6 at age 60; RR, 1.3; 95% CI, 1.1-1.5 at age 70). Breast cancer associations with detailed family history were strongest for women with first-and second-degree family history compared with no history (RR, 1.9; 95% CI, 1.1-3.2 at age 40); this association weakened in higher age groups (RR, 1.2; 95% CI, 0.88-1.5 at age 70). Associations did not change substantially when adjusted for breast density. Conclusions: Even with adjustment for breast density, a history of breast cancer in both first-and second-degree relatives is more strongly associated with breast cancer than simple first-degree family history. Impact: Future efforts to improve breast cancer risk prediction models should evaluate detailed family history as a risk factor.

Original languageEnglish (US)
Pages (from-to)938-944
Number of pages7
JournalCancer Epidemiology Biomarkers and Prevention
Volume26
Issue number6
DOIs
StatePublished - Jun 1 2017

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ASJC Scopus subject areas

  • Epidemiology
  • Oncology

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