One versus two breast density measures to predict 5- and 10-year breast cancer risk

for the Breast Cancer Surveillance Consortium

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Background: One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure. Methods: We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. Results: The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6% of women (134,404 of 722,654) who decreased density categories, 15.4% (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67% with the one-density model to >1.67% with the twodensity model. Conclusion: The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. Impact: A two-density model should be considered for women whose density decreases when calculating breast cancer risk.

Original languageEnglish (US)
Pages (from-to)889-897
Number of pages9
JournalCancer Epidemiology Biomarkers and Prevention
Volume24
Issue number6
DOIs
StatePublished - Jun 1 2015

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Breast Neoplasms
Information Systems
Breast
Vital Statistics
Breast Density
Area Under Curve
Epidemiology
Biopsy
Incidence

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

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One versus two breast density measures to predict 5- and 10-year breast cancer risk. / for the Breast Cancer Surveillance Consortium.

In: Cancer Epidemiology Biomarkers and Prevention, Vol. 24, No. 6, 01.06.2015, p. 889-897.

Research output: Contribution to journalArticle

for the Breast Cancer Surveillance Consortium. / One versus two breast density measures to predict 5- and 10-year breast cancer risk. In: Cancer Epidemiology Biomarkers and Prevention. 2015 ; Vol. 24, No. 6. pp. 889-897.
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abstract = "Background: One measure of Breast Imaging Reporting and Data System (BI-RADS) breast density improves 5-year breast cancer risk prediction, but the value of sequential measures is unknown. We determined whether two BI-RADS density measures improve the predictive accuracy of the Breast Cancer Surveillance Consortium 5-year risk model compared with one measure. Methods: We included 722,654 women of ages 35 to 74 years with two mammograms with BI-RADS density measures on average 1.8 years apart; 13,715 developed invasive breast cancer. We used Cox regression to estimate the relative hazards of breast cancer for age, race/ethnicity, family history of breast cancer, history of breast biopsy, and one or two density measures. We developed a risk prediction model by combining these estimates with 2000-2010 Surveillance, Epidemiology, and End Results incidence and 2010 vital statistics for competing risk of death. Results: The two-measure density model had marginally greater discriminatory accuracy than the one-measure model (AUC, 0.640 vs. 0.635). Of 18.6{\%} of women (134,404 of 722,654) who decreased density categories, 15.4{\%} (20,741 of 134,404) of women whose density decreased from heterogeneously or extremely dense to a lower density category with one other risk factor had a clinically meaningful increase in 5-year risk from <1.67{\%} with the one-density model to >1.67{\%} with the twodensity model. Conclusion: The two-density model has similar overall discrimination to the one-density model for predicting 5-year breast cancer risk and improves risk classification for women with risk factors and a decrease in density. Impact: A two-density model should be considered for women whose density decreases when calculating breast cancer risk.",
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