Article | Published:

Epidemiology

A prediction model for underestimation of invasive breast cancer after a biopsy diagnosis of ductal carcinoma in situ: based on 2892 biopsies and 589 invasive cancers

British Journal of Cancervolume 119pages11551162 (2018) | Download Citation

Abstract

Background

Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) might be diagnosed with invasive breast cancer at excision, a phenomenon known as underestimation. Patients with DCIS are treated based on the risk of underestimation or progression to invasive cancer. The aim of our study was to expand the knowledge on underestimation and to develop a prediction model.

Methods

Population-based data were retrieved from the Dutch Pathology Registry and the Netherlands Cancer Registry for DCIS between January 2011 and June 2012.

Results

Of 2892 DCIS biopsies, 21% were underestimated invasive breast cancers. In multivariable analysis, risk factors were high-grade DCIS (odds ratio (OR) 1.43, 95% confidence interval (CI): 1.05–1.95), a palpable tumour (OR 2.22, 95% CI: 1.76–2.81), a BI-RADS (Breast Imaging Reporting and Data System) score 5 (OR 2.36, 95% CI: 1.80–3.09) and a suspected invasive component at biopsy (OR 3.84, 95% CI: 2.69–5.46). The predicted risk for underestimation ranged from 9.5 to 80.2%, with a median of 14.7%. Of the 596 invasive cancers, 39% had unfavourable features.

Conclusions

The risk for an underestimated diagnosis of invasive breast cancer after a biopsy diagnosis of DCIS is considerable. With our prediction model, the individual risk of underestimation can be calculated based on routinely available preoperatively known risk factors (https://www.evidencio.com/models/show/1074).

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    Nationaal Borstkanker Overleg Nederland. Dutch Breast Cancer Guideline, DCIS [Internet]. 2012 [cited 1 Jun 2017]. p. version 2. Available from: https://richtlijnendatabase.nl/en/richtlijn/breast_cancer/locoregional_treatment/dcis/treatment_of_dcis.html

  2. 2.

    NICE. Clinical Guideline 80; Early and Locally Advanced Breast Cancer: Diagnosis and Treatment [Internet]. 2017 [cited 1 Jun 2017]. https://www.nice.org.uk/guidance/CG80/chapter/1-Guidance#referral-diagnosis-and-preoperative-assessment

  3. 3.

    Van Luijt, P. A. et al. The distribution of ductal carcinoma in situ (DCIS) grade in 4232 women and its impact on overdiagnosis in breast cancer screening. Breast Cancer Res. 18, 47 (2016).

  4. 4.

    Erbas, B., Provenzano, E., Armes, J. & Gertig, D. The natural history of ductal carcinoma in situ of the breast: a review. Breast Cancer Res. Treat. 97, 135–144 (2006).

  5. 5.

    Sanders, M. E., Schuyler, P. A., Simpson, J. F., Page, D. L. & Dupont, W. D. Continued observation of the natural history of low-grade ductal carcinoma in situ reaffirms proclivity for local recurrence even after more than 30 years of follow up. Mod. Pathol. 28, 662–669 (2015).

  6. 6.

    Elshof, L. E. et al. Feasibility of a prospective, randomised, open-label, international multicentre, phase III, non-inferiority trial to assess the safety of active surveillance for low risk ductal carcinoma in situ—The LORD study. Eur. J. Cancer 51, 1497–1510 (2015).

  7. 7.

    Wesseling, J., Peric, A. & Tryfonidis, K. Management of Low-Risk DCIS (LORD) [Internet]. ClinicalTrials.gov. 2015 [cited 12 Apr 2017]. https://clinicaltrials.gov/show/NCT02492607

  8. 8.

    Francis, A. et al. Addressing overtreatment of screen detected DCIS: the LORIS Trial. Eur. J. Cancer 51, 2296–2303 (2015).

  9. 9.

    Soumian, S. et al. Concordance between vacuum assisted biopsy and postoperative histology: Implications for the proposed Low Risk DCIS Trial (LORIS). Eur. J. Surg. Oncol. 39, 1337–1340 (2013).

  10. 10.

    Francis, A. LORIS. A Phase III Trial of Surgery versus Active Monitoring for Low Risk Ductal Carcinoma In Situ (DCIS) [Internet] (University of Birmingham, 2014). http://www.birmingham.ac.uk/research/activity/mds/trials/crctu/trials/loris/index.aspx

  11. 11.

    Hwang, S., Partridge, A. & Thompson, A. Comparison of Operative to Monitoring and Endocrine Therapy (COMET) Trial for Low Risk DCIS [Internet]. ClinicalTrials.gov. 2016 [cited 12 Apr 2017]. https://clinicaltrials.gov/show/NCT02926911

  12. 12.

    Ryser, M. D. et al. Outcomes of active surveillance for ductal carcinoma in situ: a computational risk analysis. J. Natl. Cancer Inst. 108, djv372 (2016).

  13. 13.

    Grimm, L. J. & Shelley Hwang, E. Active aurveillance for DCIS: the importance of selection criteria and monitoring. Ann. Surg. Oncol. https://doi.org/10.1245/s10434-016-5596-2, 2–4 (2016).

  14. 14.

    Jakub, J. W. et al. A validated nomogram to predict upstaging of ductal carcinoma in situ to invasive disease. Ann. Surg. Oncol. 10, 2915–2924 (2017).

  15. 15.

    Kim, J. et al. Factors associated with upstaging from ductal carcinoma in situ following core needle biopsy to invasive cancer in subsequent surgical excision. Breast 21, 641–645 (2012).

  16. 16.

    Brennan, M. E. et al. Ductal carcinoma in situ at core-needle biopsy: meta-analysis of underestimation and predictors of invasive breast cancer. Radiology 260, 119–128 (2011).

  17. 17.

    Huo, L. et al. Predictors of invasion in patients with core-needle biopsy-diagnosed ductal carcinoma in situ and recommendations for a selective approach to sentinel lymph node biopsy in ductal carcinoma in situ. Cancer 107, 1760–1768 (2006).

  18. 18.

    Goyal, A. et al. Is there a role of sentinel lymph node biopsy in ductal carcinoma in situ?: analysis of 587 cases. Breast Cancer Res. Treat. 98, 311–314 (2006).

  19. 19.

    Meijnen, P. et al. Risk of invasion and axillary lymph node metastasis in ductal carcinoma in situ diagnosed by core-needle biopsy. Br. J. Surg. 94, 952–956 (2007).

  20. 20.

    O’Flynn, E. A. M. et al. Prediction of the presence of invasive disease from the measurement of extent of malignant microcalcification on mammography and ductal carcinoma in situ grade at core biopsy. Clin. Radiol. 64, 178–183 (2009).

  21. 21.

    Trentin, C. et al. Predictors of invasive breast cancer and lymph node involvement in ductal carcinoma in situ initially diagnosed by vacuum-assisted breast biopsy: experience of 733 cases. Breast 21, 635–640 (2012).

  22. 22.

    Lee, S. K., Yang, J. H., Woo, S. Y., Lee, J. E. & Nam, S. J. Nomogram for predicting invasion in patients with a preoperative diagnosis of ductal carcinoma in situ of the breast. Br. J. Surg. 100, 1756–1763 (2013).

  23. 23.

    Park, H. S. et al. Risk predictors of underestimation and the need for sentinel node biopsy in patients diagnosed with ductal carcinoma in situ by preoperative needle biopsy. J. Surg. Oncol. 107, 388–392 (2013).

  24. 24.

    Coufal, O. et al. A simple model to assess the probability of invasion in ductal carcinoma in situ of the breast diagnosed by needle biopsy. Biomed. Res. Int. 2014, 480840 (2014).

  25. 25.

    Osako, T. et al. Incidence and prediction of invasive disease and nodal metastasis in preoperatively diagnosed ductal carcinoma in situ. Cancer Sci. 105, 576–582 (2014).

  26. 26.

    Sato, Y. et al. Preoperatively diagnosed ductal carcinoma in situ: risk prediction of invasion and effects on axillary management. Breast Cancer 23, 761–770 (2015).

  27. 27.

    Caswell-Smith, P. & Wall, M. Ductal carcinoma in situ: Is core needle biopsy ever enough? J. Med. Imaging Radiat. Oncol. 61, 29–33 (2017).

  28. 28.

    Park, H. S. et al. A nomogram for predicting underestimation of invasiveness in ductal carcinoma in situ diagnosed by preoperative needle biopsy. Breast 22, 869–873 (2013).

  29. 29.

    Lee, S. C. & Chang, M. C. Development and validation of web-based nomograms to predict postoperative invasive component in ductal carcinoma in situ at needle breast biopsy. Healthc. Inform. Res. 20, 152–156 (2014).

  30. 30.

    Kondo, T. et al. A model to predict upstaging to invasive carcinoma in patients preoperatively diagnosed with ductal carcinoma in situ of the breast. J. Surg. Oncol. [Internet] 112, 476–480 (2015).

  31. 31.

    Muhsen, S. et al. Outcomes for women with minimal-volume ductal carcinoma in situ completely excised at core biopsy. Ann. Surg. Oncol. 24, 3888 (2017).

  32. 32.

    Casparie, M. et al. Pathology databanking and biobanking in The Netherlands, a central role for PALGA, the nationwide histopathology and cytopathology data network and archive. Cell. Oncol. 29, 19–24 (2007).

  33. 33.

    Van der Sanden, G. A. C., Coebergh, J. W. W., Schouten, L. J., Visser, O. & Van Leeuwen, F. E. Cancer incidence in the Netherlands in 1989 and 1990: first results of the nationwide Netherlands cancer registry. Eur. J. Cancer 31, 1822–1829 (1995).

  34. 34.

    Zonderland, H. M. BI-RADS classification and breast cancer. Application in the Netherlands. Ned. Tijdschr. Oncol. 6, 145–157 (2009).

  35. 35.

    Brierley, J. D., Gospodarowicz, M. K. & Wittekind, C. TNM Classification of Malignant Tumours 7th edn, John Willey & Sons, West Sussex, UK, 181–193 (2009).

  36. 36.

    Nationaal Borstkanker Overleg Nederland. Dutch Breast Cancer Guideline, Invasive Breast Cancer [Internet]. 2012 [cited 2017 Jul 7]. p. version 2. https://richtlijnendatabase.nl/en/richtlijn/breast_cancer/adjuvant_systemic_therapy.html#onderbouwing

  37. 37.

    Van Zee, K. J. Use of axillary staging in the management of ductal carcinoma in situ. JAMA Oncol. 1, 332 (2015).

Download references

Acknowledgements

The authors thank the Netherlands Comprehensive Cancer Organization and the PALGA foundation for providing a registration database and for their efforts in making the research database for this study.

Author contributions

Study conception: C.J.C.M/P.J.W., study design: C.J.C.M./J.v.R./M.B.E.M.-P./P.J.W., data coding: C.J.C.M./P.J.W., data analyses: C.J.C.M./J.v.R., data interpretation: C.J.C.M./J.v.R./M.B.E.M.-P./B.A.M.t.B./L.d.M./S.S./P.J.W., drafting article: C.J.C.M., revision article: J.v.R./M.B.E.M.-P./B.A.M.t.B./L.d.M./S.S./P.J.W.

Author information

Affiliations

  1. CMAnalyzing, Gounodstraat 16, 6904 HC, Zevenaar, The Netherlands

    • Claudia J. C. Meurs
  2. Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Wytemaweg 80, 3015 CN, Rotterdam, The Netherlands

    • Joost van Rosmalen
  3. Department of Surgery, Albert Schweitzer Hospital, PO Box 444, 3300 AK, Dordrecht, The Netherlands

    • Marian B. E. Menke-Pluijmers
  4. Department of Radiology, Albert Schweitzer Hospital, PO Box 444, 3300 AK, Dordrecht, The Netherlands

    • Bert P. M. ter Braak
  5. Department of Research, Netherlands Comprehensive Cancer Organisation, PO Box 19079, 3501 DB, Utrecht, The Netherlands

    • Linda de Munck
    •  & Sabine Siesling
  6. Laboratory of Pathology Dordrecht, Karel Lotsyweg 145, 3318 AL, Dordrecht, The Netherlands

    • Pieter J. Westenend
  7. Regional screening organization South West the Netherlands, Maasstadweg 12, 3079 DZ, Rotterdam, The Netherlands

    • Pieter J. Westenend

Authors

  1. Search for Claudia J. C. Meurs in:

  2. Search for Joost van Rosmalen in:

  3. Search for Marian B. E. Menke-Pluijmers in:

  4. Search for Bert P. M. ter Braak in:

  5. Search for Linda de Munck in:

  6. Search for Sabine Siesling in:

  7. Search for Pieter J. Westenend in:

Competing interests

The authors declare no competing interests.

Ethics approval

The study was approved by the scientific committee of PALGA (14.025 LZV1073) and the Privacy Review Board of IKNL (K14.021).

Data availability

The dataset generated for this current study are not publicly available due additional research questions to be answered, but is available from the corresponding author on reasonable request. The prediction model is available for external validation via Evidencio (model 1074).

Funding

This work was supported by the Dutch Cancer Foundation (KWF), grant SLP2015-7769.

Note

This work is published under the standard license to publish agreement. After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution 4.0 International (CC BY 4.0).

Corresponding author

Correspondence to Pieter J. Westenend.

Electronic supplementary material

About this article

Publication history

Received

Revised

Accepted

Published

Issue Date

DOI

https://doi.org/10.1038/s41416-018-0276-6