Development and Validation of a Nomogram for Predicting Overall Survival in Patients with Epithelioid Sarcoma

Introduction: Epithelioid sarcoma is a rare and aggressive sarcoma that lacks a prognostic prediction model. This study aimed to construct and validate a nomogram to predict overall survival of patients with epithelioid sarcoma. Methods: Overall,497 eligible patients diagnosed with epithelioid sarcoma between 1990 and 2016 in the Surveillance, Epidemiology, and End Results database were included in this study. A total of 331 patients were randomly assigned to the training cohort, and the remaining 166 patients were assigned to the validation cohort. Meanwhile, 28 patients diagnosed with epithelioid sarcoma from Henan Cancer hospital between 2010 and 2017 were indentified as external validation cohort. A nomogram was constructed using the training cohort and was validated both internally and externally. C-index was used to measure discrimination. Calibration curves were used to evaluate the calibration. Decision curve analysis was used to evaluate the clinical utility of the nomogram. Results: A nomogram was constructed based on six independent risk factors for overall survival, including age, tumor site, tumor size, grade, stage, and surgery. The C-index was 0.803 (95% CI 0.774–0.832) for the training cohort, 0.833 (95% CI 0.794–0.872) for the validation cohort, and 0.688 (95% CI 0.547–0.829) for the external validation cohort, suggesting good performance of the nomogram. The calibration curves indicated a good match between the predicted probability and observed probability of the 3-year and 5-year overall survival. The results of decision curve analysis revealed that the nomogram performed well in the clinical practice. Furthermore, based on the risk score, patients were stratified into low-risk (≤154 points) and high-risk groups (>154 points) with significant overall survival differences. Conclusions: For patients with epithelioid sarcoma, our proposed nomogram is a practical and reliable tool for evaluating individual prognosis.