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

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.