An Efficient Nomogram to Predict Overall Survival of Patients with Pediatric Ewing’s Sarcoma: A Population-Based Study

BACKGROUND: The objective of our study was to develop and validate a nomogram to predict the overall survival (OS) of patients with pediatric Ewing’s sarcoma (PES). METHODS: Age, gender, race, tumor stage, tumor size, tumor site, treatment method, and survival time were collected from patients diagnosed with PES between 2004 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database. A total of 772 patients were randomly allocated to a training dataset (n = 579) and a validation dataset (n = 193). Then, univariate and multivariate analyses were performed to determine the prognostic effect of the selected variables. A nomogram was constructed to estimate the OS and it was further assessed using the concordance index (C-index), calibration curves, and receiver operating characteristic (ROC). RESULTS: Age, race, tumor size, and tumor stage were included in the nomogram. The C-index was 0.77 in the OS for the training dataset. The C-index for the validation dataset of the OS prediction was 0.75. Calibration plots and ROC curves showed excellent predictive accuracy. CONCLUSION: Age, race, tumor stage, and tumor size were independent prognostic factors for patients with PES. The nomogram showed an accurate and reliable prognostic performance for PES patients.