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Breast Cancer Research and Treatment

, Volume 170, Issue 1, pp 129–141 | Cite as

Does mammographic density mediate risk factor associations with breast cancer? An analysis by tumor characteristics

  • Megan S. RiceEmail author
  • Rulla M. Tamimi
  • Kimberly A. Bertrand
  • Christopher G. Scott
  • Matthew R. Jensen
  • Aaron D. Norman
  • Daniel W. Visscher
  • Yunn-Yi Chen
  • Kathleen R. Brandt
  • Fergus J. Couch
  • John A. Shepherd
  • Bo Fan
  • Fang-Fang Wu
  • Lin Ma
  • Laura C. Collins
  • Steven R. Cummings
  • Karla Kerlikowske
  • Celine M. Vachon
Epidemiology

Abstract

Background

Though mammographic density (MD) has been proposed as an intermediate marker of breast cancer risk, few studies have examined whether the associations between breast cancer risk factors and risk are mediated by MD, particularly by tumor characteristics.

Methods

Our study population included 3392 cases (1105 premenopausal) and 8882 (3192 premenopausal) controls from four case–control studies. For established risk factors, we estimated the percent of the total risk factor association with breast cancer that was mediated by percent MD (secondarily, by dense area and non-dense area) for invasive breast cancer as well as for subtypes defined by the estrogen receptor (ER+/ER−), progesterone receptor (PR+/PR−), and HER2 (HER2+/HER2−). Analyses were conducted separately in pre- and postmenopausal women.

Results

Positive associations between prior breast biopsy and risk of invasive breast cancer as well as all subtypes were partially mediated by percent MD in pre- and postmenopausal women (percent mediated = 11–27%, p ≤ 0.02). In postmenopausal women, nulliparity and hormone therapy use were positively associated with invasive, ER+ , PR+ , and HER2− breast cancer; percent MD partially mediated these associations (percent mediated ≥ 31%, p ≤ 0.02). Further, among postmenopausal women, percent MD partially mediated the positive association between later age at first birth and invasive as well as ER+ breast cancer (percent mediated = 16%, p ≤ 0.05).

Conclusion

Percent MD partially mediated the associations between breast biopsy, nulliparity, age at first birth, and hormone therapy with risk of breast cancer, particularly among postmenopausal women, suggesting that these risk factors at least partially influence breast cancer risk through changes in breast tissue composition.

Keywords

Mammographic density Breast cancer 

Notes

Acknowledgements

We would like to thank the participants and staff of the Nurses’ Health Study, Nurses’ Health Study II, Mayo Mammography Health Study, the San Francisco Bay Area Breast Cancer SPORE, and the San Francisco Mammography Registry for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data.

Funding

This work was supported in part by the following NIH, NCI grants: R01 CA140286, R01 CA128931, and R01 CA97396 (to C.M. Vachon); R01 CA124865 and R01 CA131332 (to R.M. Tamimi); P50 CA116201 to Dr. Ingle (F.J. Couch has Project on SPORE); P50 CA58207, U01 CA63740, and P01 CA154292 (to K. Kerlikowske); P01CA087969 and UM1 CA186107 to Dr. Stampfer (supporting NHS); and R01 CA050385, UM1 CA176726, and Breast Cancer Research Foundation to Dr. Willett (supporting NHS2). Additional support was provided by the Simeon J. Fortin Charitable Foundation, Bank of America, N.A., Co-Trustee to Dr. Bertrand; Department of Defense (DAMD 17-00-1-033; to C.M. Vachon).

Compliance with ethical standards

Conflicts of Interest

The Authors declare that they have no conflict of interest.

Supplementary material

10549_2018_4735_MOESM1_ESM.docx (108 kb)
Supplementary material 1 (DOCX 107 kb)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Megan S. Rice
    • 1
    Email author
  • Rulla M. Tamimi
    • 2
    • 3
  • Kimberly A. Bertrand
    • 4
  • Christopher G. Scott
    • 5
  • Matthew R. Jensen
    • 5
  • Aaron D. Norman
    • 5
  • Daniel W. Visscher
    • 6
  • Yunn-Yi Chen
    • 7
  • Kathleen R. Brandt
    • 8
  • Fergus J. Couch
    • 5
  • John A. Shepherd
    • 9
  • Bo Fan
    • 9
  • Fang-Fang Wu
    • 5
  • Lin Ma
    • 10
  • Laura C. Collins
    • 11
  • Steven R. Cummings
    • 12
  • Karla Kerlikowske
    • 13
  • Celine M. Vachon
    • 5
  1. 1.Clinical and Translational Epidemiology Unit, Department of MedicineMassachusetts General Hospital/Harvard Medical SchoolBostonUSA
  2. 2.Channing Division of Network MedicineBrigham and Women’s Hospital/Harvard Medical SchoolBostonUSA
  3. 3.Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonUSA
  4. 4.Slone Epidemiology Center, Boston UniversityBostonUSA
  5. 5.Department of Health Sciences ResearchMayo ClinicRochesterUSA
  6. 6.Department of Anatomic PathologyMayo ClinicRochesterUSA
  7. 7.Department of PathologyUniversity of CaliforniaSan FranciscoUSA
  8. 8.Department of RadiologyMayo ClinicRochesterUSA
  9. 9.Department of RadiologyUniversity of CaliforniaSan FranciscoUSA
  10. 10.Department of MedicineUniversity of CaliforniaSan FranciscoUSA
  11. 11.Department of PathologyHarvard Medical School, Beth Israel Deaconess Medical CenterBostonUSA
  12. 12.San Francisco Coordinating Center, California Pacific Medical Center Research InstituteSan FranciscoUSA
  13. 13.Departments of Epidemiology and Biostatistics and General Internal Medicine Section, Department of Veterans AffairsUniversity of CaliforniaSan FranciscoUSA

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