Establishment And Validation Of A Prognostic Model And Development A Web-based Survival Rate Calculator For Sarcomatoid Renal Carcinoma

Background:To develop a clinical prediction model and web-based survival rate calculator to predict the overall survival(OS)and cancer-specific survival(CSS)of sarcomatoid renal cell carcinoma(sRCC)for clinical diagnosis and treatment.Methods:Patients data of sRCC were retrieved from the Surveillance,Epidemiology,and End Results(SEER)database.Cox regression analysis was used to determine the independent factors related to survival time.The SEER training cohort was used to construct the histograph of the prediction model,and the bias of the model was tested by internal validation.At the same time,the decision analysis curve(DCA),receiver operating characteristic curve(ROC)and the model were tested and evaluated.Web-based survival computers were built to help assess disease status and clinical outcomes.RESULTS:The records of 2,742 SRCC cases were retrieved from SEER database,while 1,921 cases with a median OS of 14 and CSS of 32 months were used as the training cohort.The developed nomograms were more accurate than that of the American Joint Committee(AJCC)on Cancer staging(C-indexes of 0.767 versus 0.725 for OS and 0.775 versus 0.715 for CSS),with better discrimination than that of the AJCC stage model and the calibration was validated in the SEER validation cohort.The model’s 3-and 5-year OS and CSS were superior to AJCC and T staging on the analysis decision curve.The prognosis prediction of sRCC patients established by the prediction model could be evaluated through the web-based survival rate calculator,which plays a guiding role in clinical treatment.Conclusion:The prediction model and the web-based survival probability calculator we developed can better predict the OS and CSS of sRCC patients.