Mammographic density and risk of breast cancer by age and tumor characteristics
- Equal contributors
1 Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, 181 Longwood Ave, Boston, MA 02115, USA
2 Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA
3 Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
4 Department of Anatomic Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
5 Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
6 Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
7 Department of Radiology, University of California, 1 Irving Street, AC109San Francisco, CA 94143, USA
8 Department of Pathology, University of California, 505 Parnassus Avenue, Room M559 Box 0102, San Francisco, CA 94143, USA
9 Department of Medicine, University of California, Box 1793, 1635 Divisadero St. Suite 600, San Francisco, CA, USA
10 Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215, USA
11 San Francisco Coordinating Center, California Pacific Medical Center Research Institute, 475 Brannan Street, Suite 220, San Francisco, CA 94107, USA
12 Departments of Medicine and Epidemiology and Biostatistics, University of California, 4150 Clement Street, Mailing Code 111A1, San Francisco, CA 94121, USA
13 General Internal Medicine Section, Department of Veterans Affairs, University of California, 4150 Clement St, Mailing Code 111A1, San Francisco, CA 94121, USA
Breast Cancer Research 2013, 15:R104 doi:10.1186/bcr3570Published: 4 November 2013
Understanding whether mammographic density (MD) is associated with all breast tumor subtypes and whether the strength of association varies by age is important for utilizing MD in risk models.
Data were pooled from six studies including 3414 women with breast cancer and 7199 without who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor (HER2)) status by age (<55, 55–64, and ≥65 years).
MD was positively associated with risk of invasive tumors across all ages, with a two-fold increased risk for high (>51%) versus average density (11-25%). Women ages <55 years with high MD had stronger increased risk of ductal carcinoma in situ (DCIS) compared to women ages 55–64 and ≥65 years (Page-interaction = 0.02). Among all ages, MD had a stronger association with large (>2.1 cm) versus small tumors and positive versus negative lymph node status (P’s < 0.01). For women ages <55 years, there was a stronger association of MD with ER-negative breast cancer than ER-positive tumors compared to women ages 55–64 and ≥65 years (Page-interaction = 0.04). MD was positively associated with both HER2-negative and HER2-positive tumors within each age group.
MD is strongly associated with all breast cancer subtypes, but particularly tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages <55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women.