Mammographic density is one of the strongest risk factors for the development of breast cancer. It is thought in part to reflect the proliferative stte of epithelial and stromal cells in the breast and has been found to be associated with levels of some endogenous hormones and growth factors. It is reduced by tamoxifen therapy and by a gonadotropin-releasing hormone agonist and is increased with use of estrogen plus progesterone. Mammographic density, therefore, may be associated with both the risk and progression of breast cancer. A few, very small studies suggest mammographic density may predict recurrence among patients with invasive breast cancer. Our primary goal is to determine whether mammographic density at diagnosis of invasive breast cancer predicts risk of subsequent breast cancer events among patients participating in two large and well-characterized population-based cohorts (LACE and Pathways) within the Kaiser Permanente Northern California (KPNC) health plan membership. The combined LACE and Pathways cohorts are an ideal study population for this proposal because of the availability of patient (e.g, age, body mass index, race/ethnicity), clinical (e.g., disease stage, treatment) and behavioral factors (e.g., weight loss), as well as tumor marker data for classification of cancers into intrinic subtypes. At KPNC, members receive virtually all their health care from the plan. Further, all contents of the medical record, including mammograms, are stored indefinitely and are available for IRB- approved research.
The specific aims are to: 1) Examine the association between mammographic density and breast cancer intrinsic subtypes; 2) Examine the association between mammographic density and risk of recurrence and new primary disease; 3) Examine whether the association between mammographic density and prognosis varies by intrinsic subtype; and 4) Examine if change in density after initiation of adjuvant tamoxifen predicts treatment benefit. This will be the largest study to date on mammographic density and prognosis in patients with invasive breast cancer. It also is the first to combine measures of mammographic density with molecular classification of tumors using a 50-gene assay, enabling us to examine whether associations of breast density and prognosis vary by intrinsic subtype.
High mammographic breast density is among the strongest risk factors for breast cancer and accounts for up to one third of cases diagnosed in the U.S. Breast cancer is a heterogeneous disease and this project addresses whether breast density is associated with all or only some breast cancer subtypes. The study also addresses whether density influences breast cancer prognosis and predicts response to hormonal therapy. Study findings may improve our understanding of tumor biology in breast cancer and lead to discovery of subtype specific etiologies, as well as more tailored prevention and treatment strategies.
| Alexeeff, Stacey E; Odo, Nnaemeka U; Lipson, Jafi A et al. (2017) Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women. Cancer Epidemiol Biomarkers Prev 26:1450-1458 |
| Habel, Laurel A; Lipson, Jafi A; Achacoso, Ninah et al. (2016) Case-control study of mammographic density and breast cancer risk using processed digital mammograms. Breast Cancer Res 18:53 |
| Li, Shuai; Wong, Ee Ming; Joo, JiHoon E et al. (2015) Genetic and Environmental Causes of Variation in the Difference Between Biological Age Based on DNA Methylation and Chronological Age for Middle-Aged Women. Twin Res Hum Genet 18:720-6 |
| Hopper, John L (2015) Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations. Am J Epidemiol 182:863-7 |
