A Prognostic Nomogram based on Risk Assessment for Invasive Micropapillary Carcinoma of the Breast after Surgery

Abstract

Background: Invasive micropapillary carcinoma (IMPC) is one of the rare subtypes of breast cancer. This study aimed to explore a novel predictive nomogram model for IMPC prognosis.Methods: A total of 1855 IMPC patients diagnosed after surgery between 2004 and 2014 were identified from the Surveillance, Epidemiology and End Results (SEER) database to build and validate nomograms. All the patients included were divided into a training group (n=1300) and a validation group (n=555). A nomogram was created based on univariate and multivariate Cox proportional hazards regression analysis. In addition, receiver operating characteristic (ROC) curves were used to demonstrate the accuracy of the prognostic model. Decision curve analysis (DCA) was performed to evaluate the safety of the model in the range of clinical applications, while calibration curves were used to validate the prediction consistency.Results: Cox regression analysis indicated that age ≥62 at diagnosis, negative ER status, and tumor stage were considered adverse independent factors for overall survival (OS), while patients who were married, white or of other races, received chemotherapy or radiotherapy, had a better postoperative prognosis. The nomogram accurately predicted OS with high internal and external validation consistency index (C index) (0.756 and 0.742, respectively). The areas under the ROC curve (AUCs) of the training group were 0.787, 0.774 and 0.764 for 3 years, 5 years and 10 years, respectively, while those of the validation group were 0.756, 0.766 and 0.762, respectively. The results of both DCA and calibration curves demonstrated the good performance of the model.Conclusion: A novel nomogram for IMPC of the breast patients after surgery was developed to estimate 3- and 5-OS based on independent risk factors. This model has good accuracy and consistency in predicting prognosis and has clinical application value.