Prognosis of dedifferentiated liposarcoma based on surveillance, epidemiology, and end results database.

INTRODUCTION: This research aimed to develop and validate a novel nomogram for predicting overall survival (OS) in Dedifferentiated liposarcoma (DDLPS) patients. METHODS: A retrospective cohort of 1,155 DDLPS cases diagnosed from 2004 to 2015 was identified through the Surveillance, Epidemiology, and End Results (SEER) registry. The prognostic model was subsequently developed by incorporating covariates independently associated with survival outcomes, as determined through multivariate analysis. To assess the model's predictive performance and clinical utility, we employed a suite of validation metrics. RESULTS: Cox regression revealed age, tumor size, laterality, AJCC stage, combined summary stage, radiation, chemotherapy, and surgery as independent predictive variables for DDLPS. The C-index of the nomogram in the training and validation cohorts was 0.708 and 0.704, which was higher than that of the AJCC system. All AUC values、NRI (> 50%), IDI (> 10%), calibration and DCA curves showed that the new model had an excellent ability to predict OS. CONCLUSIONS: Our study represents the initial effort to develop a nomogram for predicting OS in DDLPS patients based on the SEER database. Significantly, the nomogram showed a greater potential for accurately predicting survival as opposed to the AJCC system.