Nomogram for predicting breast-conservation surgery after neoadjuvant chemotherapy.

Abstract

Background: The indications for neoadjuvant systemic treatment (NST) have broadened to early breast cancer patients and more patients can undergo breast conservation with results in better cosmetic outcomes. However, a significant number of patients with operable breast cancer still require mastectomy after NST with a small number of patients experiencing disease progression which may hinder complete surgical resection. Therefore, accurate prediction of each patient’s likelihood of achieving breast conservation after NST is important for establishing a treatment plan for patients with operable breast cancers. Methods: We identified 534 women from the Seoul National University Hospital Breast Care Center, who were stage II and III, and treated with neoadjuvant chemotherapy and surgery from Jan. 2001 to Dec. 2010. Breast conservation surgery (BCS) and tumor size reduction to less than 3cm were clinical outcome variables for nomograms, and we analyzed the various clinicopathologic factors best predicting these outcomes. To develop well-calibrated and exportable nomograms for BCS and for residual tumor size, we built each model in a training cohort and validated it in an independent validation cohort. Results: Of the 513 patients, pCR was observed in 10.5% and BCS was performed in 50.1%. The nomogram for predicting BCS and tumor size reduction to less than 3cm were constructed using logistic regressing model. Initial tumor size(p<0.001), the distance between the lesion and the nipple (p < 0.001), the presence of suspicious calcifications in the mammography (p = 0.0127) and multicentricity (p = 0.0146) were independently associated with breast conservation surgery. ER status (p = 0.001), initial tumor size (p < 0.001), histologic type (p = 0.012) were independently associated with a residual tumor size <3cm. Mastectomy rate in the larger than 3cm tumors were 72.7%, and breast conservation surgery in smaller than 3cm tumors were 63.2%. (p < 0.001). Conclusions: In conclusion, we have established a new model to predict BCS and residual tumor size after NST. The model showed the outperformed prediction accuracy compared with previous similar models with reflecting novel factors impacting on surgical decision making.