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Preoperative MRI in breast cancer: effect of breast density on biopsy rate and yield

Abstract

Purpose

Preoperative breast MRI is used to evaluate for additional cancer and extent of disease for newly diagnosed breast cancer, yet benefits and harms of preoperative MRI are not well-documented. We examined whether preoperative MRI yields additional biopsy and cancer detection by extent of breast density.

Methods

We followed women in the Breast Cancer Surveillance Consortium with an incident breast cancer diagnosed from 2005 to 2017. We quantified breast biopsies and cancers detected within 6 months of diagnosis by preoperative breast MRI receipt, overall and by breast density, accounting for MRI selection bias using inverse probability weighted logistic regression.

Results

Among 19,324 women with newly diagnosed breast cancer, 28% had preoperative MRI, 11% additional biopsy, and 5% additional cancer detected. Four times as many women with preoperative MRI underwent additional biopsy compared to women without MRI (22.6% v. 5.1%). Additional biopsy rates with preoperative MRI increased with increasing breast density (27.4% for extremely dense compared to 16.2% for almost entirely fatty breasts). Rates of additional cancer detection were almost four times higher for women with v. without MRI (9.9% v. 2.6%). Conditional on additional biopsy, age-adjusted rates of additional cancer detection were lowest among women with extremely dense breasts, regardless of imaging modality (with MRI: 35.0%; 95% CI 27.0–43.0%; without MRI: 45.1%; 95% CI 32.6–57.5%).

Conclusion

For women with dense breasts, preoperative MRI was associated with much higher biopsy rates, without concomitant higher cancer detection. Preoperative MRI may be considered for some women, but selecting women based on breast density is not supported by evidence.

Trial registration

ClinicalTrials.gov: NCT02980848; registered 2017.

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Fig. 1

Data availability

Publicly-available data and instructions for requesting additional data are available at: Breast Cancer Surveillance Consortium (BCSC) Data:: BCSC (bcsc-research.org).

Code availability

Not applicable.

Reproducible research statement

Study protocol and statistical code: Available on request, please contact kpwa.scc@kp.org with specific queries.

Data set

Available after study aims of funded grants are addressed and with appropriate contracts.

References

  1. 1.

    Martin LJ, Boyd NF (2008) Mammographic density. Potential mechanisms of breast cancer risk-associated with mammographic density: hypotheses based on epidemiological evidence. Breast Cancer Res 10(1):201

    Article  Google Scholar 

  2. 2.

    Hwang ES, Miglioretti DL, Ballard-Barbash R, Weaver DL, Kerlikowske K, National Cancer Institute Breast Cancer Surveillance C (2007) Association between breast density and subsequent breast cancer following treatment for ductal carcinoma in situ. Cancer Epidemiol Biomark Prev 16(12):2587–93

    Article  Google Scholar 

  3. 3.

    Rahbar H, Hippe DS, Alaa A, Cheeney SH, van der Schaar M, Partridge SC, Lee CI (2020) The value of patient and tumor factors in predicting preoperative breast MRI outcomes. Radiol Imaging Cancer 2(4):e1900999

    Article  Google Scholar 

  4. 4.

    Elmi A, Conant EF, Kozlov A, Young AJ, Long Q, Doot RK, McDonald ES (2020) Preoperative breast MR imaging in newly diagnosed breast cancer: comparison of outcomes based on mammographic modality, breast density and breast parenchymal enhancement. Clin Imaging 70:18–24. https://doi.org/10.1016/j.clinimag.2020.10.021

    Article  PubMed  Google Scholar 

  5. 5.

    https://www.nejm.org/doi/full/10.1056/nejmoa065447

  6. 6.

    Liberman L (2006) Breast MR imaging in assessing extent of disease. Magn Reson Imaging Clin N Am 14(3):339–349

    Article  Google Scholar 

  7. 7.

    Houssami N, Ciatto S, Macaskill P, Lord SJ, Warren RM, Dixon JM, Irwig L (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):3248–3258

    Article  Google Scholar 

  8. 8.

    Brennan ME, Houssami N, Lord S, Macaskill P, Irwig L, Dixon JM, Warren RM, Ciatto S (2009) Magnetic resonance imaging screening of the contralateral breast in women with newly diagnosed breast cancer: systematic review and meta-analysis of incremental cancer detection and impact on surgical management. J Clin Oncol 27(33):5640–5649

    Article  Google Scholar 

  9. 9.

    Anaout A, Catley C, Booth CM, McInnes M, Graham I, Kumar V, Simos D, Van Walraven C, Clemons M (2015) Use of preoperative magnetic resonance imaging for breast cancer. A Canadian population-based study. JAMA Oncol 1(9):1238–1250

    Article  Google Scholar 

  10. 10.

    Deurloo EE, Peterse JL, Rutgers EJT, Besnard APE, Muller SH, Gilhuijs KA (2005) Additional breast lesions in patients eligible for breast-conserving therapy by MRI: impact of preoperative management and potential benefit of computerised analysis. Eur J Cancer 41(10):1393–1401

    Article  Google Scholar 

  11. 11.

    DeMartini W, Lehman C (2008) A review of current evidence-based clinical applications for breast magnetic resonance imaging. Top Magn Reson Imaging 19(3):143–150

    Article  Google Scholar 

  12. 12.

    Debald M, Abramian A, Nemes L et al (2015) Who may benefit from preoperative breast MRI? A single-center analysis of 1102 consecutive patients with primary breast cancer. Breast Cancer Res Treat 153:531–537

    Article  Google Scholar 

  13. 13.

    Gutierrez RL, DeMartini WB, Silbergeld JJ, Eby PR, Peacock S, Javid SH, Lehman CD (2010) High cancer yield and positive predictive value: outcomes at a center routinely using preoperative breast MRI for staging. Am J Roent 196:W93–W99

    Article  Google Scholar 

  14. 14.

    National Comprehensive Cancer Network. NCCN guidelines for breast cancer (version 2.2015). 2015 Contract No.: October 15, 2014

  15. 15.

    Houssami N, Hayes DF (2009) Review of preoperative magnetic resonance imaging (MRI) in breast cancer: should MRI be performed on all women with newly diagnosed, early stage breast cancer? CA Cancer J Clin 59(5):290–302

    Article  Google Scholar 

  16. 16.

    Breast Cancer Surveillance Consortium (BCSC). https://bcsc-research.org/. Accessed 11 Oct 2020

  17. 17.

    National Institute for Health Research. Good research practice guidelines. https://www.nihr.ac.uk/health-and-care-professionals/learning-and-support/good-clinical-practice.htm. Accessed 11 Oct 2020

  18. 18.

    American College of Radiology (2013) Breast Imaging Reporting and Data System® (BI-RADS®). American College of Radiology, Reston

    Google Scholar 

  19. 19.

    Breast Cancer Surveillance Consortium. https://www.bcsc-research.org/application/files/4516/0096/5722/BCSC_Data_Definitions_v3__2020.09.23.pdf. Accessed 12 Dec 2020

  20. 20.

    Oehlert GW (1992) A note on the delta method. Am Stat 46:27–29

    Google Scholar 

  21. 21.

    Lehman CD, Gatsonis C, Kuhl CK, Hendrick RE, Pisano ED, Hanna L, Peacock S, Smazal SF, Maki DD, Julian TB, DePeri ER, Bluemke DA, Schnall MD, ACRIN Trial 6667 Investigators Group (2007) MRI evaluation of the contralateral breast in women with recently diagnosed breast cancer. N Engl J Med 356(13):1295–303

    CAS  Article  Google Scholar 

  22. 22.

    Montgomery M, McCrone SH (2010) Psychological distress associated with the diagnostic phase for suspected breast cancer: systematic review. J Adv Nurs 66(11):2372–2390

    Article  Google Scholar 

  23. 23.

    Bond M, Pavey T, Welch K, Cooper C, Garside R, Dean S, Hyde C (2013) Systematic review of the psychological consequences of false-positive screening mammograms. Health Technol Assess 17(13):1–170

    CAS  Article  Google Scholar 

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Acknowledgements

Research reported in this work was funded through a Patient-Centered Outcomes Research Institute (PCORI) Program Award (PCS-1504-30370). Data collection for this research was additionally supported by the Breast Cancer Surveillance Consortium with funding from the National Cancer Institute (P01CA154292, U54CA163303, R01CA149365) and the Agency for Health Research and Quality (R01 HS018366-01A1). The collection of cancer and vital status data used in this study was supported in part by several state public health departments and cancer registries throughout the U.S. For a full description of these sources, please see: https://www.bcsc-research.org/about/work-acknowledgement. All statements in this report, including its findings and conclusions, are solely those of the authors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute (PCORI), its Board of Governors or Methodology Committee, nor those of the National Cancer Institute or the National Institutes of Health. We thank the participating women, mammography facilities, and radiologists for the data they have provided for this study. You can learn more about the BCSC at: http://www.bcsc-research.org/. The collection of cancer incidence and vital status data used in this study was supported, in part, by: (a) 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 HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement U58-DP003862-01 awarded to the California Department of Public Health; (b) The Vermont Cancer Registry, supported in part by Cooperative Agreement NU58DP006322 from the Centers for Disease Control and Prevention, awarded to the Vermont State Agency of Human Services. (c) The Cancer Surveillance System of the Fred Hutchinson Cancer Research Center, which is funded by contracts N01-CN-005230, N01-CN-67009, N01-PC-35142, HHSN261201000029C, and HHSN261201300012I from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute with additional support from the Fred Hutchinson Cancer Research Center and the State of Washington; (d) The New Hampshire State Cancer Registry supported in part by cooperative agreement U55/CCU-121912 awarded to the New Hampshire Department of Health and Human Services, Division of Public Health Services, Bureau of Disease Control and Health Statistics, Health Statistics and Data Management Section; (e) The North Carolina Central Cancer Registry, which is partially supported by the Centers for Disease Control and Prevention under cooperative agreement DP12-120503CONT14; (f) Manuscripts including data from the Metro Chicago Breast Cancer Registry were supported in part by the Illinois Department of Public Health, Illinois State Cancer Registry which is partially supported by the Centers for Disease Control and Prevention under cooperative agreement DP12-120504CONT15. The ideas and opinions expressed herein are those of the authors and endorsement by the State of California, the California Department of Public Health; Illinois Department of Public Health; New Hampshire Department of Health and Human Services; the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors is not intended nor should be inferred. We thank the participating women, mammography facilities, and radiologists for the data they have provided for this study.

Funding

Primary funding source: PCORI CS-1504-30370.

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Contributions

All authors whose names appear on the submission: (1) made substantial contributions to the conception or design of the work; or the acquisition, analysis, or interpretation of data; or the creation of new software used in the work; (2) drafted the work or revised it critically for important intellectual content; (3) approved the version to be published; and (4) agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Corresponding author

Correspondence to Tracy Onega.

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Conflict of interest

Authors report no conflicts of interest or competing interests.

Consent for publication

All authors consent to publication of this manuscript.

Ethics approval and consent to participate

The institutional review boards of the participating Breast Cancer Surveillance Consortium (BCSC) registries and Statistical Coordinating Center approved all study activities through passive consent (three registries) or waiver of written consent (two registries and the Statistical Coordinating Center). This study was Health Insurance Portability and Accountability Act compliant. Registries and the Statistical Coordinating Center received a federal Certificate of Confidentiality and other protections for the identities of women, physicians, and facilities. Our study was registered on ClinicalTrials.gov (NCT02980848) and followed the Good Research Practices guidelines for comparative effectiveness research.

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The National Cancer Institute had no role in the study’s design; the collection, analysis, or interpretation of the data; the writing of the manuscript; or the decision to submit the manuscript for publication. Likewise, the content in this manuscript is solely the responsibility of the authors and does not necessarily represent the views of PCORI, its Board of Governors or Methodology Committee.

Appendix

Appendix

See Tables 5, 6 and 7.

Table 5 Study population characteristics for women with breast cancer (13,869) without preoperative MRIa,b overall and by breast density from 2005 to 2017
Table 6 Study population characteristics for women with breast cancer (13,869) with preoperative MRIa,b overall and by breast density from 2005 to 2017
Table 7 Adjusted rates* (per 100 women) of for biopsy type in relation to pre-operative imaging modality using inverse weighted probability regression methods among women who had an additional biopsy (N = 1943) stratified by BIRADS breast density categories

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Onega, T., Zhu, W., Kerlikowske, K. et al. Preoperative MRI in breast cancer: effect of breast density on biopsy rate and yield. Breast Cancer Res Treat (2021). https://doi.org/10.1007/s10549-021-06418-x

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Keywords

  • Preoperative MRI
  • Breast density
  • Breast biopsy
  • Occult cancer
  • Breast Cancer Surveillance Consortium
  • Cancer detection rate