Dense and Non-dense Mammographic Area and Risk of Breast Cancer by Age and Tumor Characteristics.


Bertrand KA, Scott CG, Tamimi RM, Jensen MR, Pankratz SV, Norman AD, Visscher DW, Couch FJ, Shepherd J, Chen Y-Y, Fan B, Wu F-F, Ma L, Beck AH, Cummings SR, Kerlikowske K, Vachon CM. Dense and Non-dense Mammographic Area and Risk of Breast Cancer by Age and Tumor Characteristics. Cancer Epidemiol Biomarkers Prev 2015;

Date Published:

2015 Feb 25


Background:Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent MD with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages <55 years. To provide insight into these associations, we examined the components of percent MD (dense area (DA) and non-dense area (NDA) with breast cancer subtypes. Methods:Data were pooled from six studies including 4095 breast cancers and 8558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathological characteristics and receptor status were calculated using polytomous logistic regression. Results:DA was associated with increased breast cancer risk [odds ratios (OR) for quartiles: 0.65, 1.00(Ref), 1.22, 1.55; p-trend <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00(Ref), 0.88, 0.72; p-trend <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (p-trend<0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER+ vs. ER- tumors [p-heterogeneity (het) = 0.02] while NDA was more strongly associated with decreased risk of ER- vs. ER+ tumors [p-het = 0.03]. Conclusions:DA and NDA have differential associations with ER+ vs. ER- tumors that vary by age. Impact:DA and NDA are important to consider when developing age- and subtype-specific risk models.