A New Model to Predict Survival Time in Patients With Hepatocellular Carcinoma With BCLC Advanced Stage

Area of Science:

• Hepatobiliary Medicine
• Oncology
• Biostatistics

Background:

• Advanced-stage hepatocellular carcinoma (HCC) presents diverse treatment challenges.
• The advent of multimolecular targeted agents necessitates improved survival prediction models.

Purpose of the Study:

• To develop and validate novel survival prediction models for HCC patients.
• To aid in treatment planning and efficacy evaluation in the era of targeted therapies.

Main Methods:

• Analysis of a dataset comprising 518 HCC patients diagnosed before 2017.
• Utilized multiple regression analysis to identify independent survival predictors.
• Employed a Weibull model for best fit and established two predictive survival models.

Main Results:

• Identified key predictors of survival including tumor size, nodule count, macrovascular invasion, extrahepatic metastasis, total bilirubin, albumin, prothrombin time (PT), alpha-fetoprotein, and des-gamma-carboxyprothrombin (DCP).
• Developed two distinct survival prediction models, one incorporating PT and DCP, the other excluding them.
• The Weibull model demonstrated the best fit for survival prediction.

Conclusions:

• The established models provide a valuable tool for predicting survival in advanced HCC.
• These models are instrumental for optimizing treatment strategies and evaluating therapeutic efficacy in the context of modern targeted therapies.