Grant Number:	1R01CA168893-01 Interpret this number
Primary Investigator:	Habel, Laurel
Organization:	Kaiser Foundation Research Institute
Project Title:	Mammographic Density & Prognosis Among Breast Cancer Intrinsic Subtypes
Fiscal Year:	2012

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: 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.




Examination of fully automated mammographic density measures using LIBRA and breast cancer risk in a cohort of 21,000 non-Hispanic white women.
Authors: Habel L.A. , Alexeeff S.E. , Achacoso N. , Arasu V.A. , Gastounioti A. , Gerstley L. , Klein R.J. , Liang R.Y. , Lipson J.A. , Mankowski W. , et al. .
Source: Breast Cancer Research : Bcr, 2023-08-06 00:00:00.0; 25(1), p. 92.
EPub date: 2023-08-06 00:00:00.0.
PMID: 37544983
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Identification of 31 loci for mammographic density phenotypes and their associations with breast cancer risk.
Authors: Sieh W. , Rothstein J.H. , Klein R.J. , Alexeeff S.E. , Sakoda L.C. , Jorgenson E. , McBride R.B. , Graff R.E. , McGuire V. , Achacoso N. , et al. .
Source: Nature Communications, 2020-10-09 00:00:00.0; 11(1), p. 5116.
EPub date: 2020-10-09 00:00:00.0.
PMID: 33037222
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Alcohol and Tobacco Use in Relation to Mammographic Density in 23,456 Women.
Authors: McBride R.B. , Fei K. , Rothstein J.H. , Alexeeff S.E. , Song X. , Sakoda L.C. , McGuire V. , Achacoso N. , Acton L. , Liang R.Y. , et al. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2020-02-17 00:00:00.0; , .
EPub date: 2020-02-17 00:00:00.0.
PMID: 32066618
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Reproductive Factors and Mammographic Density: Associations Among 24,840 Women and Comparison of Studies Using Digitized Film-Screen Mammography and Full-Field Digital Mammography.
Authors: Alexeeff S.E. , Odo N.U. , McBride R. , McGuire V. , Achacoso N. , Rothstein J.H. , Lipson J.A. , Liang R.Y. , Acton L. , Yaffe M.J. , et al. .
Source: American Journal Of Epidemiology, 2019-06-01 00:00:00.0; 188(6), p. 1144-1154.
PMID: 30865217
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Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women.
Authors: Alexeeff S.E. , Odo N.U. , Lipson J.A. , Achacoso N. , Rothstein J.H. , Yaffe M.J. , Liang R.Y. , Acton L. , McGuire V. , Whittemore A.S. , et al. .
Source: Cancer Epidemiology, Biomarkers & Prevention : A Publication Of The American Association For Cancer Research, Cosponsored By The American Society Of Preventive Oncology, 2017 Sep; 26(9), p. 1450-1458.
EPub date: 2017-07-11 00:00:00.0.
PMID: 28698185
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Case-control study of mammographic density and breast cancer risk using processed digital mammograms.
Authors: Habel L.A. , Lipson J.A. , Achacoso N. , Rothstein J.H. , Yaffe M.J. , Liang R.Y. , Acton L. , McGuire V. , Whittemore A.S. , Rubin D.L. , et al. .
Source: Breast Cancer Research : Bcr, 2016-05-21 00:00:00.0; 18(1), p. 53.
EPub date: 2016-05-21 00:00:00.0.
PMID: 27209070
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Genetic And Environmental Causes Of Variation In The Difference Between Biological Age Based On Dna Methylation And Chronological Age For Middle-aged Women
Authors: Li S. , Wong E.M. , Joo J.E. , Jung C.H. , Chung J. , Apicella C. , Stone J. , Dite G.S. , Giles G.G. , Southey M.C. , et al. .
Source: Twin Research And Human Genetics : The Official Journal Of The International Society For Twin Studies, 2015 Dec; 18(6), p. 720-6.
PMID: 26527295
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Odds per adjusted standard deviation: comparing strengths of associations for risk factors measured on different scales and across diseases and populations.
Authors: Hopper J.L. .
Source: American Journal Of Epidemiology, 2015-11-15 00:00:00.0; 182(10), p. 863-7.
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