Geffen Kleinstern1,2, Christopher G Scott2, Rulla M Tamimi3,4, Matthew R Jensen2, V Shane Pankratz5, Kimberly A Bertrand6, Aaron D Norman2, Daniel W Visscher7, Fergus J Couch8, Kathleen Brandt9, John Shepherd10, Fang-Fang Wu11, Yunn-Yi Chen12, Steven R Cummings13, Stacey Winham2, Karla Kerlikowske14, Celine M Vachon15. 1. School of Public Health, University of Haifa, Haifa, Israel. 2. Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA. 3. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 4. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 5. University of New Mexico, Albuquerque, NM, USA. 6. Slone Epidemiology Center, Boston University School of Medicine, Boston, MA, USA. 7. Department of Anatomic Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA. 8. Department of Laboratory Medicine and Pathology, Mayo Clinic College of Medicine, Rochester, MN, USA. 9. Department of Radiology, Mayo Clinic College of Medicine, Rochester, MN, USA. 10. University of Hawaii, Honolulu, HI, USA. 11. Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN, 55905, USA. 12. Department of Pathology and Laboratory Services, University of California, San Francisco, CA, USA. 13. San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA. 14. Departments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans Affairs, University of California, San Francisco, CA, USA. 15. Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic College of Medicine, 200 First St. SW, Rochester, MN, 55905, USA. vachon.celine@mayo.edu.
Abstract
PURPOSE: We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes. METHODS: We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group. RESULTS: All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers. CONCLUSIONS: Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.
PURPOSE: We evaluated the association of percent mammographic density (PMD), absolute dense area (DA), and non-dense area (NDA) with risk of "intrinsic" molecular breast cancer (BC) subtypes. METHODS: We pooled 3492 invasive BC and 10,148 controls across six studies with density measures from prediagnostic, digitized film-screen mammograms. We classified BC tumors into subtypes [63% Luminal A, 21% Luminal B, 5% HER2 expressing, and 11% as triple negative (TN)] using information on estrogen receptor (ER), progesterone receptor (PR), humanepidermal growth factor receptor 2 (HER2), and tumor grade. We used polytomous logistic regression to calculate odds ratio (OR) and 95% confidence intervals (CI) for density measures (per SD) across the subtypes compared to controls, adjusting for age, body mass index and study, and examined differences by age group. RESULTS: All density measures were similarly associated with BC risk across subtypes. Significant interaction of PMD by age (P = 0.001) was observed for Luminal A tumors, with stronger effect sizes seen for younger women < 45 years (OR = 1.69 per SD PMD) relative to women of older ages (OR = 1.53, ages 65-74, OR = 1.44 ages 75 +). Similar but opposite trends were seen for NDA by age for risk of Luminal A: risk for women: < 45 years (OR = 0.71 per SD NDA) was lower than older women (OR = 0.83 and OR = 0.84 for ages 65-74 and 75 + , respectively) (P < 0.001). Although not significant, similar patterns of associations were seen by age for TN cancers. CONCLUSIONS: Mammographic density measures were associated with risk of all "intrinsic" molecular subtypes. However, findings of significant interactions between age and density measures may have implications for subtype-specific risk models.
Entities:
Keywords:
Breast cancer; Mammographic density; “Intrinsic” molecular subtypes
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