Analysis of prognostic factors of undifferentiated pleomorphic sarcoma and construction and validation of a prediction nomogram based on SEER database

Objective: The purpose of this study was to construct and validate a nomogram for predicting overall survival (OS) in undifferentiated pleomorphic sarcoma (UPS) patients at 3, 5 years after the diagnosis. Method: According to the inclusion and exclusion criteria, 1079 patients with UPS were screened from the SEER database and randomly divided into the training cohort (n = 755) and the validation cohort (n = 324). Patient demographic and clinicopathological characteristics were first described, and the correlation between the two groups was compared, using the Kaplan-Meier method and Cox regression analysis to determine independent prognostic factors. Based on the identified independent prognostic factors, a nomogram survival prediction model for OS in UPS patients was established using R language. The nomogram’s performance was then validated using multiple indicators, including the area under the time-dependent receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, decision-curve analysis (DCA). Results: A total of nine factors ,age, tumor location, tumor size, tumor depth, N stage, M stage, tumor grade, surgery and radiotherapy,were included in the nomogram prediction model as independent influence factor. The OS nomogram prediction model in the model group and validation cohort C-index All greater than 0 .75, the AUC was greater than 0.78, and both were higher than the C of the TNM staging system Index and AUC values. Nomogram prediction model and TNM staging system calibration curve with 4 The 5 ° lines were all relatively conforming. Decision curve analysis showed that both the nomogram model and the TNM staging system had clinical net benefits over a wide range of threshold probabilities, and the nomogram had higher clinical net benefits than the TNM staging system as a whole. Conclusion: The nomogram survival prediction model can individualize the prediction of 3-year and 5-year OS in patients with UPS, with good discrimination, accuracy and clinical practicability, which can provide a reference for clinicians and patients to make better clinical decisions.