Breast Cancer Research and Treatment

, Volume 172, Issue 2, pp 453–461 | Cite as

Associations of preoperative breast magnetic resonance imaging with subsequent mastectomy and breast cancer mortality

  • Shi-Yi WangEmail author
  • Jessica B. Long
  • Brigid K. Killelea
  • Suzanne B. Evans
  • Kenneth B. Roberts
  • Andrea L. Silber
  • Amy J. Davidoff
  • Tannaz Sedghi
  • Cary P. Gross



To examine associations between pre-operative magnetic resonance imaging (MRI) use and clinical outcomes among women undergoing breast-conserving surgery (BCS) with or without radiotherapy for early-stage breast cancer.


We identified women from the Surveillance, Epidemiology, and End Results-Medicare dataset aged 67–94 diagnosed during 2004–2010 with stage I/II breast cancer who received BCS. We compared subsequent mastectomy and breast cancer mortality with versus without pre-operative MRI, using Cox regression and competing risks models. We further stratified by receipt of radiotherapy for subgroup analyses.


Our sample consisted of 24,379 beneficiaries, 4691 (19.2%) of whom received pre-operative MRI. Adjusted rates of subsequent mastectomy and breast cancer mortality were not significantly different with and without MRI: 3.2 versus 4.1 per 1000 person-years [adjusted hazard ratio (AHR) 0.92; 95% confidence interval (CI) 0.70–1.19] and 5.3 versus 8.7 per 1000 person-years (AHR 0.89; 95% CI 0.73–1.08), respectively. In subgroup analyses, women receiving BCS plus radiotherapy had similar rates of subsequent mastectomy (AHR 1.17; 95% CI 0.84–1.61) and breast cancer mortality (AHR 1.00; 95% CI 0.80–1.24) with versus without MRI. However, among women receiving BCS alone, MRI use was associated with lower risks of subsequent mastectomy (AHR 0.60; 95% CI 0.37–0.98) and breast cancer mortality (AHR 0.57; 95% CI 0.36–0.92).


Pre-operative MRI was associated with improved outcomes among older women with breast cancer receiving BCS alone, but not among those receiving BCS plus radiotherapy. Further research is needed to identify appropriate settings for which MRI may be helpful.


Magnetic resonance imaging Outcomes research Competing risks models Risk stratification 



The collection of the California cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under Contract N01-PC-35136 awarded to the Northern California Cancer Center, Contract N01-PC-35139 awarded to the University of Southern California, and contract N02-PC-15105 awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement #U55/CCR921930-02 awarded to the Public Health Institute. The authors of this report are responsible for its content. The ideas and opinions expressed herein are those of the author(s) and endorsement by the State of California, Department of Public Health the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors is not intended nor should be inferred. The authors acknowledge the efforts of the Applied Research Program, NCI; the Office of Research, Development and Information, CMS; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database. The interpretation and reporting of the SEER-Medicare data are the sole responsibility of the authors.


This investigation was supported by a Pilot Grant and a P30 Cancer Center Support Grant (CCSG), both from Yale Comprehensive Cancer Center.

Compliance with ethical standards

Conflict of interest

Dr. Wang receives research support from Genentech. Dr. Gross receives support from Medtronic, Inc., Johnson & Johnson, Inc., and twenty-first Century Oncology. These sources of support were not used for any portion of the current manuscript. None of the other coauthors have conflicts to report.

Ethical approval

The Yale Human Investigation Committee determined that this study did not directly involve human subjects. Thus, tis article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

10549_2018_4919_MOESM1_ESM.pdf (86 kb)
Supplementary material 1 (PDF 86 KB)


  1. 1.
    Solin LJ. Counterview (2010) Pre-operative breast MRI (magnetic resonance imaging) is not recommended for all patients with newly diagnosed breast cancer. Breast 19(1):7–9CrossRefGoogle Scholar
  2. 2.
    Sardanelli F (2010) Overview of the role of pre-operative breast MRI in the absence of evidence on patient outcomes. Breast 19(1):3–6CrossRefGoogle Scholar
  3. 3.
    Hede K (2009) Preoperative MRI in breast cancer grows contentious. J Natl Cancer Inst 101(24):1667–1669CrossRefGoogle Scholar
  4. 4.
    Lehman CD, DeMartini W, Anderson BO, Edge SB (2009) Indications for breast MRI in the patient with newly diagnosed breast cancer. JNCCN 7(2):193–201PubMedGoogle Scholar
  5. 5.
    Houssami N, Ciatto S, Macaskill P et al (2008) Accuracy and surgical impact of magnetic resonance imaging in breast cancer staging: systematic review and meta-analysis in detection of multifocal and multicentric cancer. J Clin Oncol 26(19):3248–3258CrossRefGoogle Scholar
  6. 6.
    Wang SY, Virnig BA, Tuttle TM, Jacobs DR Jr, Kuntz KM, Kane RL (2013) Variability of preoperative breast MRI utilization among older women with newly diagnosed early-stage breast cancer. Breast J 19:627–636CrossRefGoogle Scholar
  7. 7.
    Killelea BK, Long JB, Chagpar AB et al (2013) Trends and clinical implications of preoperative breast MRI in Medicare beneficiaries with breast cancer. Breast Cancer Res Treat 141(1):155–163CrossRefGoogle Scholar
  8. 8.
    Hwang N, Schiller DE, Crystal P, Maki E, McCready DR (2009) Magnetic resonance imaging in the planning of initial lumpectomy for invasive breast carcinoma: its effect on ipsilateral breast tumor recurrence after breast-conservation therapy. Ann Surg Oncol 16(11):3000–3009CrossRefGoogle Scholar
  9. 9.
    Turnbull L, Brown S, Harvey I et al (2010) Comparative effectiveness of MRI in breast cancer (COMICE) trial: a randomised controlled trial. Lancet 375(9714):563–571CrossRefGoogle Scholar
  10. 10.
    Wang SY, Kuntz KM, Tuttle TM, Jacobs DR Jr, Kane RL, Virnig BA (2013) The association of preoperative breast magnetic resonance imaging and multiple breast surgeries among older women with early stage breast cancer. Breast Cancer Res Treat 138(1):137–147CrossRefGoogle Scholar
  11. 11.
    Wang SY, Long JB, Killelea BK et al (2016) Preoperative breast magnetic resonance imaging and contralateral breast cancer occurrence among older women with breast cancer. J Clin Oncol 34(4):321–328CrossRefGoogle Scholar
  12. 12.
    Houssami N, Turner R, Macaskill P et al (2014) An individual person data meta-analysis of preoperative magnetic resonance imaging and breast cancer recurrence. J Clin Oncol 35:392–401CrossRefGoogle Scholar
  13. 13.
    Hughes KS, Schnaper LA, Berry D et al (2004) Lumpectomy plus tamoxifen with or without irradiation in women 70 years of age or older with early breast cancer. N Engl J Med 351(10):971–977CrossRefGoogle Scholar
  14. 14.
    Kunkler IH, Williams LJ, Jack WJ, Cameron DA, Dixon JM (2015) Breast-conserving surgery with or without irradiation in women aged 65 years or older with early breast cancer (PRIME II): a randomised controlled trial. Lancet Oncol 16(3):266–273CrossRefGoogle Scholar
  15. 15.
    Overview of the SEER Program. Accessed 25 Jan
  16. 16.
    Smith BD, Gross CP, Smith GL, Galusha DH, Bekelman JE, Haffty BG (2006) Effectiveness of radiation therapy for older women with early breast cancer. J Natl Cancer Inst 98(10):681–690CrossRefGoogle Scholar
  17. 17.
    Srokowski TP, Fang S, Duan Z et al (2008) Completion of adjuvant radiation therapy among women with breast cancer. Cancer 113(1):22–29CrossRefGoogle Scholar
  18. 18.
    Punglia RS, Saito AM, Neville BA, Earle CC, Weeks JC (2010) Impact of interval from breast conserving surgery to radiotherapy on local recurrence in older women with breast cancer: retrospective cohort analysis. BMJ 340:c845CrossRefGoogle Scholar
  19. 19.
    Bach PB, Guadagnoli E, Schrag D, Schussler N, Warren JL (2002) Patient demographic and socioeconomic characteristics in the SEER-Medicare database applications and limitations. Med Care 40(8 Suppl):IV–I19CrossRefGoogle Scholar
  20. 20.
    Elixhauser A, Steiner C, Harris DR, Coffey RM (1998) Comorbidity measures for use with administrative data. Med Care 36(1):8–27CrossRefGoogle Scholar
  21. 21.
    Davidoff AJ, Zuckerman IH, Pandya N et al (2013) A novel approach to improve health status measurement in observational claims-based studies of cancer treatment and outcomes. J Geriatr Oncol 4(2):157–165CrossRefGoogle Scholar
  22. 22.
    Roberts KB, Soulos PR, Herrin J et al (2013) The adoption of new adjuvant radiation therapy modalities among Medicare beneficiaries with breast cancer: clinical correlates and cost implications. Int J Radiat Oncol Biol Phys 85(5):1186–1192CrossRefGoogle Scholar
  23. 23.
    Early Breast Cancer Trialists’ Collaborative G, Peto R, Davies C et al. Comparisons between different polychemotherapy regimens for early breast cancer: meta-analyses of long-term outcome among 100,000 women in 123 randomised trials. Lancet 2012;379(9814):432–444CrossRefGoogle Scholar
  24. 24.
    Howlader N, Ries LA, Mariotto AB, Reichman ME, Ruhl J, Cronin KA (2010) Improved estimates of cancer-specific survival rates from population-based data. J Natl Cancer Inst 102(20):1584–1598CrossRefGoogle Scholar
  25. 25.
    Surveillance, Epidemiology, and End Results Program. SEER Cause-specific Death Classification.

Copyright information

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

Authors and Affiliations

  • Shi-Yi Wang
    • 1
    • 2
    Email author
  • Jessica B. Long
    • 2
    • 3
  • Brigid K. Killelea
    • 2
    • 4
  • Suzanne B. Evans
    • 2
    • 5
  • Kenneth B. Roberts
    • 2
    • 5
  • Andrea L. Silber
    • 2
    • 6
  • Amy J. Davidoff
    • 2
    • 7
  • Tannaz Sedghi
    • 2
  • Cary P. Gross
    • 2
    • 3
  1. 1.Department of Chronic Disease EpidemiologyYale University School of Public HealthNew HavenUSA
  2. 2.Cancer Outcomes, Public Policy, and Effectiveness Research (COPPER) CenterYale Cancer Center and Yale University School of MedicineNew HavenUSA
  3. 3.Section of General Internal Medicine, Department of Internal MedicineYale University School of MedicineNew HavenUSA
  4. 4.Department of SurgeryYale University School of MedicineNew HavenUSA
  5. 5.Department of Therapeutic RadiologyYale University School of MedicineNew HavenUSA
  6. 6.Section of Medical Oncology, Department of Internal MedicineYale University School of MedicineNew HavenUSA
  7. 7.Department of Health Policy and ManagementYale University School of Public HealthNew HavenUSA

Personalised recommendations