Lusine Yaghjyan1, Rulla M Tamimi2,3, Kimberly A Bertrand4, Christopher G Scott5, Matthew R Jensen5, V Shane Pankratz5, Kathy Brandt6, Daniel Visscher7, Aaron Norman8, Fergus Couch8,9, John Shepherd10, Bo Fan11, Yunn-Yi Chen11, Lin Ma12, Andrew H Beck13, Steven R Cummings14, Karla Kerlikowske15,16, Celine M Vachon8. 1. Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, 2004 Mowry Road, Gainesville, FL, 32610, USA. lyaghjyan@ufl.edu. 2. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA, 02115, USA. 3. Department of Epidemiology, Harvard T.H Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA. 4. Slone Epidemiology Center at Boston University, Boston, MA, USA. 5. Division of Biomedical Statistics and Informatics, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN, 55905, USA. 6. Department of Radiology, Mayo Clinic, Rochester, MN, 55905, USA. 7. Department of Anatomic Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN, 55905, USA. 8. Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN, 55905, USA. 9. Division of Experimental Pathology, Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN, 55905, USA. 10. Department of Radiology, University of California, 1 Irving Street, AC109, San Francisco, CA, 94143, USA. 11. Department of Pathology, University of California, 505 Parnassus AvenueRoom M559, Box 0102, San Francisco, CA, 94143, USA. 12. Department of Medicine, University of California, 1635 Divisadero St. Suite 600, Box 1793, San Francisco, CA, USA. 13. Department of Pathology, Beth Israel Deaconess Medical Center and Harvard Medical School, 330 Brookline Avenue, Boston, MA, 02215, USA. 14. San Francisco Coordinating Center, California Pacific Medical Center Research Institute, 475 Brannan Street, Suite 220, San Francisco, CA, 94107, USA. 15. Departments of Medicine and Epidemiology and Biostatistics, University of California, 4150 Clement Street, Mailing Code 111A1, San Francisco, CA, 94121, USA. 16. General Internal Medicine Section, Department of Veterans Affairs, University of California, 4150 Clement Street, Mailing Code 111A1, San Francisco, CA, 94121, USA.
Abstract
PURPOSE: We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy. METHODS: This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses' Health Study, Nurses' Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy. RESULTS: Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant. CONCLUSION: Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.
PURPOSE: We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy. METHODS: This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses' Health Study, Nurses' Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy. RESULTS: Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant. CONCLUSION: Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.
Entities:
Keywords:
Breast cancer subtypes; Breast density; Postmenopausal hormone therapy; Tumor aggressiveness
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