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 journalArticle

Abstract

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
Volume41
Issue number1
DOIs
StatePublished - 2015
Externally publishedYes

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Breast Neoplasms
Segmental Mastectomy
Calcinosis
Carcinoma, Intraductal, Noninfiltrating
Margins of Excision
Netherlands
Calibration
Area Under Curve
Counseling
Logistic Models
Recurrence
Neoplasms

Keywords

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

ASJC Scopus subject areas

  • Oncology
  • Surgery

Cite this

Barentsz, M. W., Postma, E. L., Van Dalen, T., Van Den Bosch, M. A. A. J., Miao, H., Gobardhan, P. D., ... Verkooijen, H. M. (2015). Prediction of positive resection margins in patients with non-palpable breast cancer. European Journal of Surgical Oncology, 41(1), 106-112. https://doi.org/10.1016/j.ejso.2014.07.474

Prediction of positive resection margins in patients with non-palpable breast cancer. / Barentsz, M. W.; Postma, E. L.; Van Dalen, T.; Van Den Bosch, M. A A J; Miao, H.; Gobardhan, P. D.; Van Den Hout, L. E.; Pijnappel, R. M.; Witkamp, A. J.; Van Diest, P. J.; Van Hillegersberg, R.; Verkooijen, H. M.

In: European Journal of Surgical Oncology, Vol. 41, No. 1, 2015, p. 106-112.

Research output: Contribution to journalArticle

Barentsz, MW, Postma, EL, Van Dalen, T, Van Den Bosch, MAAJ, Miao, H, Gobardhan, PD, Van Den Hout, LE, Pijnappel, RM, Witkamp, AJ, Van Diest, PJ, Van Hillegersberg, R & Verkooijen, HM 2015, 'Prediction of positive resection margins in patients with non-palpable breast cancer', European Journal of Surgical Oncology, vol. 41, no. 1, pp. 106-112. https://doi.org/10.1016/j.ejso.2014.07.474
Barentsz MW, Postma EL, Van Dalen T, Van Den Bosch MAAJ, Miao H, Gobardhan PD et al. Prediction of positive resection margins in patients with non-palpable breast cancer. European Journal of Surgical Oncology. 2015;41(1):106-112. https://doi.org/10.1016/j.ejso.2014.07.474
Barentsz, M. W. ; Postma, E. L. ; Van Dalen, T. ; Van Den Bosch, M. A A J ; Miao, H. ; Gobardhan, P. D. ; Van Den Hout, L. E. ; Pijnappel, R. M. ; Witkamp, A. J. ; Van Diest, P. J. ; Van Hillegersberg, R. ; Verkooijen, H. M. / Prediction of positive resection margins in patients with non-palpable breast cancer. In: European Journal of Surgical Oncology. 2015 ; Vol. 41, No. 1. pp. 106-112.
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abstract = "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.",
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AU - Postma, E. L.

AU - Van Dalen, T.

AU - Van Den Bosch, M. A A J

AU - Miao, H.

AU - Gobardhan, P. D.

AU - Van Den Hout, L. E.

AU - Pijnappel, R. M.

AU - Witkamp, A. J.

AU - Van Diest, P. J.

AU - Van Hillegersberg, R.

AU - Verkooijen, H. M.

PY - 2015

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N2 - 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.

AB - 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.

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