Prediction of positive resection margins in patients with non-palpable breast cancer. Issue 1 (January 2015)

• Record Type: Journal Article
• Authors: 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.
• Is Part Of: European journal of surgical oncology. Volume 41:Issue 1(2015:Jan.)
• Page Start: 106
• Page End: 112
• Publication Date: 2015-01
• Subjects: Oncology -- Periodicals; Cancer -- Surgery -- Periodicals; Medical Oncology -- Periodicals; Neoplasms -- surgery -- Periodicals; Cancer -- Chirurgie -- Périodiques; Cancérologie -- Périodiques; Oncologie; Chirurgie (geneeskunde); Electronic journals; Electronic journals -- Sciences; Electronic journals -- Medicine; Electronic journals; 616.994059005
• DOI: 10.1016/j.ejso.2014.08.474
• Languages: English
• ISSNs: 0748-7983

Abstract

<abstract xml:lang="en" abstract-type="author" id="abs0010"> <title id="sectitle0010">Abstract</title> <sec> <title id="sectitle0015">Background</title> <p id="abspara0010">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.</p> </sec> <sec> <title id="sectitle0020">Methods</title> <p id="abspara0015">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.</p> </sec> <sec> <title id="sectitle0025">Results</title> <p id="abspara0020">Positive resection margins were present in 69/576 (12%) patients. Factors independently associated with positive resection margins included mammographic microcalcifications (OR 2.14, 1.22–3.77), tumour size (OR 1.75, 1.20–2.56), presence of DCIS (OR 2.61, 1.41–4.82), Bloom and Richardson grade 2/3 (OR 1.82, 1.05–3.14), and caudal location of the lesion (OR 2.4, 1.35–4.27). The model was well calibrated and moderately able to discriminate between patients with positive versus negative resection margins (AUC 0.70, 95% CI, 0.63–0.77, and 0.69 after internal validation).</p> </sec> <sec> <title id="sectitle0030">Conclusion</title> <p id="abspara0025">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.</p> </sec> </abstract>