Nomograms predicting survival for all four subtypes of breast cancer: a SEER-based population study

The prognosis of female breast cancer (BC) patients is determined by many clinicopathological factors. In this study, we aimed to identify prognostic factors for BC and develop reliable nomograms to predict the 1-, 3-, and 5-year overall survival (OS) and breast cancer-specific survival (BCSS).

The Surveillance, Epidemiology, and End Results (SEER) database was used to screen 227,989 eligible patients as the study cohort. The whole cohort was randomly divided into a training cohort (n=113,996) and a testing cohort (n=113,993). The log-rank test and Cox proportional hazards analysis were applied to select variables and build nomogram models based on the training cohort. Internal and external validation were performed to evaluate the performance of the models by calculating the C-index and generating calibration plots in the training cohort and testing cohort.

The following factors were included in both the OS and BCSS nomograms: subtypes of BC, metastasis (bone, liver, lung, and brain), age at diagnosis, race, tumor size, grade, number of positive lymph nodes, and marital status. The calibration plots presented excellent consistency between the actual and nomogram-predicted survival probabilities in both the training cohort and testing cohort. The C-index values of the nomograms were 0.796 and 0.793 for OS and 0.856 and 0.853 for BCSS in the training and testing cohorts, respectively.

The established nomograms provide a visualization of the risk of each prognostic factor and can assist clinicians in predicting the 1-, 3-, and 5-year OS and BCSS for all 4 subtypes of BC.