A nomogram to predict prognosis in Ewing sarcoma of bone

Objective: This study was designed to develop a nomogram for assessing the survival of patients with Ewing sarcoma (ES). Methods: Data from patients diagnosed with ES between 2004 and 2013 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Based on patient registration, the primary cohort was divided into a training set (n = 479, data from 17 cancer registries) and a validation set (n = 137, data from 1 cancer registry). Then, the prognostic effects of variables were analyzed using Kaplan-Meier method and Cox proportional hazard model. Moreover, nomograms were established for estimating 3- and 5-year overall survival (OS) and cancer-special survival (CSS) based on Cox regression model. Last, nomogram was validated by training set and validation set. Results: According to the multivariate analysis of training set, nomogram which combined age, race, stage, tumor site, tumor size and chemotherapy was identified. The internal bootstrap resampling approach suggested the nomogram had sufficient discriminatory power with the C-index of OS: 0.754 (95% CI, 0.705-0.802) and CSS: 0.759 (95% CI, 0.700-0.800). The calibration plots also demonstrated good consistence between the prediction and the observation. Conclusion: Our nomogram is a reliable and powerful tool for distinguishing and predicting the survival of ES patients, thus helping to better select medical examinations and optimize treatment options in collaboration with medical oncologists and surgeons.