Objectives: This study aimed to evaluate and update incidence trends of soft-tissue sarcoma (STS) and to develop a nomogram to predict cancer-specific survival (CSS) in patients diagnosed with primary STS of the liver.Methods: Patients with hepatic STS were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Joinpoint regression analyses were performed to assess the incidence trends of STS. A nomogram was developed based on the independent risk factors chosen by Cox regression models. The calibration curve, area under the receiver operating characteristic curve (AUC), C-index, and decision curve analysis (DCA) were used to assess the predictive performance of the nomogram.Results: The incidence of STS increased between 1994 and 2012. There was a sudden decline in the incidence of STS from 2013. The incidence of STS was different in distinct races and genders. The nomogram for predicting the CSS of hepatic STS according to the independent factors was well calibrated and it displayed optimal discrimination power.Conclusion: This study highlights that age, sex, tumor size, quality of surgery, and histologic subtypes may contribute to the prognosis of hepatic STS, and STS may be etiologically distinct and should be considered separately in different races and genders.
Keywords: SEER; Soft-tissue sarcoma; incidence; liver.