Back to Authors

Cummings, Steve

Mayo Clinic

California Pacific Medical Center

Citations 3

Abstract IA22: Mammographic density: A risk factor for all breast cancers or only specific subtypes?
Vachon, Celine M. , Chen, Yunn‐Yi , Jensen, Matthew R. , Visscher, Daniel W., Shepherd, John, Fan, Bo , Wu, Fangfang , Beck, Andrew H. , Cummings, Steve, Vachon, Celine M. , Tamimi, Rulla M. , Scott, Christopher G. , Bertrand, Kimberly A. , Norman, Aaron D. , Couch, Fergus J. , Wu, Fang-Fang, Pankratz, V. Shane , Kerlikowske, Karla

Cancer Epidemiology, Biomarkers & Prevention | May 20, 2016 | Volume: 25 | Issue: 3_Supplement | Pages: IA22-IA22

10.1158/1538-7755.disp15-ia22 Get It

Abstract Gene expression profiling has identified molecular subtypes that classify invasive breast cancers into distinct categories that vary in their clinical behavior and response to treatment. These subtypes highlight the many possible biologically and clinically distinct types of breast cancer. Immunohistochemical (IHC) staining of tumor sections using antibody panels has been used as a surrogate for the molecular subtypes identified through gene expression profiling, resulting in a set of intrinsic molecular subtypes. Given the heterogeneity within breast cancer, one might expect that different risk factors influence specific subtypes of breast cancer through various etiologic pathways. We evaluated whether percent mammographic density (MD), the proportion of fibroglandular or white tissue on a mammogram and one of the strongest and most consistent risk factors for breast cancer, is associated equally with all intrinsic molecular subtypes. Data were pooled from six cohort or case-control studies including 3389 women with invasive breast cancer and 9860 without, who underwent screening mammography. Percent MD was assessed from digitized film-screen mammograms (for cases, at a median 4 years prior to diagnosis) using a computer-assisted threshold technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+. Receptor status was abstracted from clinical pathology records and supplemented by IHC staining of tumor sections or microarrays. With estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor (HER2) information, we classified tumors into the intrinsic molecular subtypes: Luminal A ( ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (ER-/PR-/HER2-). For cancers found to be triple negative (TN), we also stained for epidermal growth factor receptor (EGFR) and cytokeratins (CK) 5/6 to differentiate basal-like tumors (positive for EGFR and/or CK 5/6) from the unclassifieds (negative on both EGFR and CK 5/6). We used polytomous logistic regression to calculate the odds (OR) of each of the intrinsic subtypes of breast cancer by categories of percent MD, adjusting for age, BMI and study. Contrasts were constructed and tested within the polytomous model framework to investigate differences in the strength of association of percent MD across subtypes. On average, cases were slightly older (56.4 years [SD=11.3]) than controls (55.8 [10.9]). Of the 3389 invasive breast cancer cases, 2146 (63%) were classified as Luminal A, 709 (21%) as Luminal B, 169 (5%) as HER-2 expressing, and 365(11%) as triple negative (TN). Of the TN tumors, 203 had tumor tissue available and were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) as unclassified. Percent (%) MD was associated with breast cancer risk across all intrinsic subtypes. For Luminal A, compared to women with 11-25% MD (reference), women with 0-10% MD had a reduced risk of breast cancer (OR=0.64 [95% confidence interval (CI): 0.55, 0.74]) while women with 26-50% MD had an OR=1.5 (1.3,1.7) and women with 51%+ MD had the highest risk, OR=2.4 (2.0, 2.8). Similar associations were seen for Luminal B, HER2 expressing, and TN across percent MD categories. The small differences among the percent MD-breast cancer associations observed for the different subtypes were not statistically significant, either when comparing the four (Luminal A, Luminal B, HER-2 expressing and TN; p=0.61) or five categories of subtypes (Luminal A, Luminal B, HER-2 expressing, basal-like, unclassified; p=0.66). Our results suggest percent MD is a risk factor for all intrinsic molecular subtypes. Additional study is needed to examine whether these results hold for younger and older aged women. Understanding the importance of mammographic density measures for subtypes of breast cancer has significance for development of subtype-specific risk models. Citation Format: Celine Vachon, Rulla Tamimi, Yunn-Yi Chen, Christopher Scott, Kimberly Bertrand, Matthew Jensen, Daniel Visscher, Aaron Norman, Fergus Couch, John Shepherd, Bo Fan, Fang-Fang Wu, Lin Ma, Andrew Beck, Steve Cummings, V. Shane Pankratz, Karla Kerlikowske. Mammographic density: A risk factor for all breast cancers or only specific subtypes? [abstract]. In: Proceedings of the Eighth AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 13-16, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2016;25(3 Suppl):Abstract nr IA22.
A Meta-Analysis of the Association of Fracture Risk and Body Mass Index in Women
Johansson, Helena , Kanis, John А. , Odén, Anders, McCloskey, Eugène , Cummings, Steve, Eisman, John A. , Fujiwara, Saeko , Glüer, Claus‐C. , Krieg, Marc-Antoine, Kröger, Heikki , LaCroix, Andrea Z. , Lau, Edith, Leslie, William D. , Melton, L. Joseph, O’Neill, Terence W , Pasco, Julie A. , Reid, David M., Rivadeneira, Fernando , Staa, Tjeerd van , Yoshimura, Noriko , Chapurlat, Roland D , Christiansen, Claus , Díez‐Pérez, Adolfo , Goltzman, David , Hans, Didier B. , Khaw, Kay‐Tee , Mellström, Dan , Prior, Jerilynn C. , Zillikens, M. Carola , Leslie, William D

Journal of Bone and Mineral Research | June 17, 2013 | Volume: 29 | Issue: 1 | Pages: 223-233

10.1002/jbmr.2017 Get It

ABSTRACT Several recent studies suggest that obesity may be a risk factor for fracture. The aim of this study was to investigate the association between body mass index (BMI) and future fracture risk at different skeletal sites. In prospective cohorts from more than 25 countries, baseline data on BMI were available in 398,610 women with an average age of 63 (range, 20–105) years and follow up of 2.2 million person-years during which 30,280 osteoporotic fractures (6457 hip fractures) occurred. Femoral neck BMD was measured in 108,267 of these women. Obesity (BMI ≥ 30 kg/m2) was present in 22%. A majority of osteoporotic fractures (81%) and hip fractures (87%) arose in non-obese women. Compared to a BMI of 25 kg/m2, the hazard ratio (HR) for osteoporotic fracture at a BMI of 35 kg/m2 was 0.87 (95% confidence interval [CI], 0.85–0.90). When adjusted for bone mineral density (BMD), however, the same comparison showed that the HR for osteoporotic fracture was increased (HR, 1.16; 95% CI, 1.09–1.23). Low BMI is a risk factor for hip and all osteoporotic fracture, but is a protective factor for lower leg fracture, whereas high BMI is a risk factor for upper arm (humerus and elbow) fracture. When adjusted for BMD, low BMI remained a risk factor for hip fracture but was protective for osteoporotic fracture, tibia and fibula fracture, distal forearm fracture, and upper arm fracture. When adjusted for BMD, high BMI remained a risk factor for upper arm fracture but was also a risk factor for all osteoporotic fractures. The association between BMI and fracture risk is complex, differs across skeletal sites, and is modified by the interaction between BMI and BMD. At a population level, high BMI remains a protective factor for most sites of fragility fracture. The contribution of increasing population rates of obesity to apparent decreases in fracture rates should be explored. © 2014 American Society for Bone and Mineral Research.
Breast Cancer Risk by Breast Density, Menopause, and Postmenopausal Hormone Therapy Use
Cummings, Steve, Vachon, Celine M. , Vacek, Pamela M. , Miglioretti, Diana L. , Kerlikowske, Karla , Cook, Andrea J. , Buist, Diana S.M. , Vachon, Celine M. , Miglioretti, Diana L

Journal of Clinical Oncology | July 20, 2010 | Volume: 28 | Issue: 24 | Pages: 3830-3837

10.1200/jco.2009.26.4770 Get It

Purpose We determined whether the association between breast density and breast cancer risk and cancer severity differs according to menopausal status and postmenopausal hormone therapy (HT) use. Methods We collected data on 587,369 women who underwent 1,349,027 screening mammography examinations; 14,090 women were diagnosed with breast cancer. We calculated 5-year breast cancer risk from a survival model for subgroups of women classified by their Breast Imaging Reporting and Data System (BIRADS) breast density, age, menopausal status, and current HT use, assuming a body mass index of 25 kg/m 2 . Odds of advanced (ie, IIb, III, IV) versus early (ie, I, IIa) stage invasive cancer was calculated according to BIRADS density. Results Breast cancer risk was low among women with low density (BIRADS-1): women age 55 to 59 years, 5-year risk was 0.8% (95% CI, 0.6 to 0.9%) for non-HT users and 0.9% (95% CI, 0.7% to 1.1%) for estrogen and estrogen plus progestin users. Breast cancer risk was high among women with very high density (BIRADS-4), particularly estrogen plus progestin users: women age 55 to 59 years, 5-year risk was 2.4% (95% CI, 2.0% to 2.8%) for non-HT users, 3.0% (95% CI, 2.6% to 3.5%) for estrogen users, and 4.2% (95% CI, 3.7% to 4.6%) for estrogen plus progestin users. Advanced-stage breast cancer risk was increased 1.7-fold for postmenopausal HT users who had very high density (BIRADS-4) compared to those with average density (BIRADS-2). Conclusion Postmenopausal women with high breast density are at increased risk of breast cancer and should be aware of the added risk of taking HT, especially estrogen plus progestin.