Establishing a novel prognostic tool for Ewing sarcoma patients: Surveillance, Epidemiology, and End Results database analysis

Patients diagnosed with Ewing sarcoma (ES) usually experience poor outcomes. Accurate prediction of ES patients’ prognosis is essential to improve their survival. Given that ES is a relatively rare tumor with a low incidence, we aim at developing a prognostic nomogram of ES patients based on a large sample analysis. We used the Surveillance, Epidemiology, and End Results (SEER) database to screen eligible patients diagnosed ES of bone. This retrospective study presented the clinicopathological characteristics and prognosis of ES. We randomly assigned all ES patients to 2 sets (training set and validation set) with an equal number of patients. In order to identify independent factors of survival, we performed univariate and multivariate Cox analysis in the training set. Then, we constructed novel nomograms to predict survival of ES patients by integrating significant independent variables from the training set. The prognostic performance of constructed nomograms was examined using concordance index (C-index) and calibration curves in both training and validation set. We included a total of 988 eligible cases diagnosed ES of bone between 2000 and 2015. Age >18 years, distant metastasis, tumor size >10 cm, and no surgery were independent risk factors for poorer survival. Our survival prediction nomograms were established based on those 4 independent risk factors. Good calibration plots were achieved in internal and external validation. The internal validation C-indexes of the nomogram for overall survival (OS) and cancer-specific survival (CSS) were 0.733 and 0.737, respectively. Similar good results were also achieved in external validation setting. The established nomograms show good performance and allow for better evaluating the prognosis of ES patients and recommending appropriate instructions.