Construction of a survival prediction model for patients with hepatocellular carcinoma (HCC) based on real clinical data: a single-center retrospective study.

Abstract

Background: Given the rising incidence of hepatocellular carcinoma (HCC) globally, especially in China, information about independent risk factors for survival and disease prognosis of the illness is scarce. In the field of HCC research, there is an urgent need for a scientific basis to enhance the accuracy of clinical diagnosis, optimize the course of therapy, and accurately predict the prognosis. Against this backdrop, the objective of this work was to develop a scientific, efficient, and methodical nomogram to forecast the survival prognosis of HCC.

Methods: A real-world study collected clinical data from January 1, 2011, to December 31, 2019, for individuals with HCC. Overall survival (OS) was determined using Kaplan-Meier analysis. Independent risk variables were identified using Cox proportional hazards regression. A nomogram predicting 1-, 3-, and 5-year OS was created. The reliability of the predictions of the model was assessed using receiver operating characteristic (ROC), calibration, and decision curve analysis (DCA).

Results: Data from 1,128 HCC cases showed 1-, 3-, and 5-year OS rates were 86.3%, 65.3%, and 43.1%, respectively. Univariate Cox regression identified 13 variables influencing HCC survival including age, HCC screening status, hepatitis C virus (HCV) status, nonalcoholic fatty liver disease (NAFLD) and alcoholic liver disease (ALD) status, liver cirrhosis, elevated alpha-fetoprotein (AFP), Child-Pugh grade, tumor size, tumor number, treatment method, tumor thrombus, and extrahepatic metastasis (P<0.05). Multivariate analysis confirmed HCC screening status, tumor size, ALD, Child-Pugh classification, and therapy method as independent prognostic factors (P<0.05). The nomogram achieved an area under the ROC curve (AUC) of 0.868. Calibration curves of the 1-, 3-, and 5-year survival times and the DCA curve confirmed its predictive accuracy.

Conclusions: Patients without HCC screening, tumor size >5 cm, ALD, Child-Pugh grade C, and conservative treatment had a poor survival prognosis. A nomogram based on these risk variables provides a reliable tool for predicting the survival chances of patients with HCC.