A novel nomogram for predicting locoregional recurrence risk in breast cancer patients treated with neoadjuvant chemotherapy and mastectomy

Background: This study aimed to establish a nomogram for predicting locoregional recurrence (LRR) in breast cancer patients treated with neoadjuvant chemotherapy (NAC) and mastectomy. Methods: A total of 2368 patients who received NAC and mastectomy between 2000 and 2014 from 12 grade A tertiary hospitals in China were analyzed retrospectively. The nomogram was developed based on the patients treated in three cancer hospitals (training set, n = 1629) and validated based on patients from the other nine general hospitals (validation set, n = 739). Factors identified from Fine and Gray's competing risk analysis were used to establish the nomogram. The predictive performance of the nomogram model was compared with the cTNM stage, ypTNM stage, and the Neo-Bioscore model by using the area under the time dependent receiver operating characteristic curves (tAUC), calibration curve, and decision curve analysis (DCA). Results: The nomogram incorporated six risk factors derived from multivariable analysis of the training set including age, ypT stage, ypN stage, lymph node ratio, postmastectomy radiotherapy, and endocrine therapy. In the training set, the AUC of the nomogram was 0.792, which was higher than the values of the cTNM stage (0.582), ypTNM stage (0.737), and the Neo-Bioscore prognosis model (0.658). In the validation set, the AUC of the cTNM (0.619); ypTNM (0.636); and Neo-Bioscore staging system (0.584) were also significantly lower than the AUC of the nomogram (0.705). Both in the training and validation sets, the calibration curve showed good agreement between the nomogram-based predictions and the actual observations. Conclusion: The novel nomogram provides a more accurate evaluation of LRR for breast cancer patients treated with NAC and mastectomy. (c) 2021 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 161 (2021) 191-197