Breast cancer (BC) has become the most common malignancy worldwide, accounting for 11.7% of newly diagnosed cancer cases last year. Invasive ductal carcinoma (IDC) is the most common pathological type of BC. However, there were few studies to predict distant metastatic sites and overall survival (OS) of IDC patients.
Post-operative IDC patients from 2010 to 2016 in the Surveillance, Epidemiology, and End Results (SEER) database were reviewed. Nomograms were developed to predict the specific distant metastatic sites and OS of IDC patients. The performance of nomograms was evaluated with the calibration curves, area under the curve (AUC), and decision curve analysis (DCA). Kaplan-Meier analysis and log-rank tests were used to estimate the survival times of IDC patients with distant metastases.
A total of 171,967 post-operative IDC patients were enrolled in our study. Univariate and multivariate analyses were used to establish the nomograms of significant variables. The AUC of the nomograms for the prediction of liver, lung, bone, and brain metastases was 0.903, 0.877, 0.863, and 0.811, respectively. In addition, the AUC of the nomogram for the prediction of 1-, 3-, and 5-year OS was 0.809, 0.813, 0.787, respectively. Calibration curves and DCA showed good consistency and clinical benefits, respectively.
We constructed new predictive models for liver, lung, brain, bone metastases and 1-, 3-, and 5-year OS in IDC patients. These can help clinicians to individualize the treatment of IDC patients, so that patients can get the more appropriate treatment options.