A Visualized Dynamic Prediction Model for Lymphatic Metastasis in Ewing's Sarcoma for Smart Medical Services - Li, Wenle; Xu, Chan; Hu, Zhaohui; Dong, Shengtao; Wang, Haosheng; Liu, Qiang; Tang, Zhi-Ri; Li, Wanying; Wang, Bing; Lei, Zhi; Yin, Chengliang (Frontiers in Public Health, 2022)
Background-This study was aimed at predicting the prognosis of Ewing's sarcoma (ES) by nomogram. The risk of lymphatic metastasis in patients with ES was predicted by the built model, which provided guidance for the clinical diagnosis and treatment planning. Methods-A total of 929 patients diagnosed with ES were enrolled from the year of 2010 to 2016 in the Surveillance, Epidemiology, and End Results (SEER) database. The nomogram was established to determine predictive factors of lymphatic metastasis according to univariate and multivariate logistic regression analysis. The validation of the model performed using multicenter data (n=51). Receiver operating characteristics (ROC) curves and calibration plots were used to evaluate the prediction accuracy of the nomogram. Decision curve analysis (DCA) was implemented to illustrate the practicability of the nomogram clinical application. Based on the nomogram, a web calculator was also established and visualization. Results-In this study, the nomogram was established based on five independent factors (survival time, race, T stage, M stage, surgery, and lung metastasis), which were identified for lymphatic metastasis in ES patients. The model showed significant diagnostic accuracy with the value of the area under the ROC curve (AUC) was 0.743 (95%CI: 0.714-0.771) for SEER internal validation and 0.763 (95%CI: 0.623-0.871) for multicenter data external validation. The calibration plot and DCA indicated that the model had vital clinical application value. Conclusion-In this study, we constructed and developed a nomogram with risk factors to predict lymphatic metastasis in ES patients and validated accuracy of itself. It can help clinicians make better decisions to provide more accurate prognosis and treatment for ES patients.