Prediction of positive resection margins in patients with non-palpable breast cancer

M. W. Barentsz, E. L. Postma, T. Van Dalen, M. A A J Van Den Bosch, H. Miao, P. D. Gobardhan, L. E. Van Den Hout, R. M. Pijnappel, A. J. Witkamp, P. J. Van Diest, R. Van Hillegersberg, H. M. Verkooijen

Research output: Contribution to journalArticlepeer-review


Background: In patients undergoing breast conserving surgery for non-palpable breast cancer, obtaining tumour free resection margins is important to prevent reexcision and local recurrence. We developed a model to predict positive resection margins in patients undergoing breast conserving surgery for non-palpable invasive breast cancer. Methods: A total of 576 patients with non-palpable invasive breast cancer underwent breast conserving surgery in five hospitals in the Netherlands. A prediction model for positive resection margins was developed using multivariate logistic regression. Calibration and discrimination of the model were assessed and the model was internally validated by bootstrapping. Results: Positive resection margins were present in 69/576 (12%) patients. Factors independently associated with positive resection margins included mammographic microcalcifications (OR 2.14, 1.22e3.77), tumour size (OR 1.75, 1.20e2.56), presence of DCIS (OR 2.61, 1.41e4.82), Bloom and Richardson grade 2/3 (OR 1.82, 1.05e3.14), and caudal location of the lesion (OR 2.4, 1.35e4.27). The model was well calibrated and moderately able to discriminate between patients with positive versus negative resection margins (AUC 0.70, 95% CI, 0.63e0.77, and 0.69 after internal validation). Conclusion: The presented prediction model is moderately able to differentiate between women with high versus low risk of positive margins, and may be useful for surgical planning and preoperative patient counselling.

Original languageEnglish (US)
Pages (from-to)106-112
Number of pages7
JournalEuropean Journal of Surgical Oncology
Issue number1
StatePublished - 2015
Externally publishedYes


  • Breast cancer
  • Non-palpable lesions
  • Prediction model
  • Tumour margins

ASJC Scopus subject areas

  • Oncology
  • Surgery

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