Development and verification of prognostic nomogram for extraskeletal Ewing's sarcoma based on the SEER database

Background: Extraskeletal Ewing's sarcoma (EES) is a rare tumor, and there is currently no predictive model for overall survival of EES patients. This study sought to use data from the Surveillance, Epidemiology, and End Results (SEER) database to develop a clinical predictive model that could be used to assess the prognosis of EES patients. Methods: We selected and downloaded prognostic data on 356 patients diagnosed with extraskeletal Ewing's sarcoma based on screening criteria, These patients were distributed between 2004 and 2015. 356 patients were randomly divided into a training cohort (70 %) and an internal validation cohort (30 %). After univariate or multifactor Cox regression analysis, the relevant variables were screened and a nomogram was constructed. The consistency index (C-index), calibration chart and receiver operating characteristic (ROC) curve were used to evaluate the established nomogram. The clinical utility of the model was verified by clinical decision curve.Study conducted and outcomes reported according to STROBE statement. Results: After multifactor regression analysis, we identified five factors that were significantly associated with EES prognosis, and subsequently established a nomogram. Verification data showed that the C-index of this nomogram was 0.829 (95 % CI 0.774-0.884). the AUCs of the nomogram for predicting the 3- and 5-year OS were 0.91 and 0.863. the calibration curves and Decision curve analysis showed that nomogram could predict the prognosis of EES patients. Conclusion: Stage, age, tumour size, chemotherapy, and surgery may be independent prognostic factors for EES. our study produced a survival nomogram that can be used to predict the prognosis of patients with EES and validated its performance, which may help clinicians evaluate the condition of patients with EES and choose personalised treatment.