Prediction models of hepatocellular carcinoma development in chronic hepatitis B patients

Area of Science:

• Hepatology and Viral Hepatitis Research
• Oncology and Cancer Risk Prediction
• Medical Diagnostics and Biomarkers

Background:

• Chronic hepatitis B virus (HBV) infection is a leading cause of liver cirrhosis and hepatocellular carcinoma (HCC).
• Universal antiviral therapy and HCC surveillance strategies for all chronic hepatitis B (CHB) patients are globally burdensome.
• Accurate risk stratification is essential for effective CHB patient management and resource allocation.

Purpose of the Study:

• To review existing and novel HCC prediction models for CHB patients.
• To identify tools for classifying HCC development risk in CHB.
• To introduce noninvasive scoring systems incorporating liver stiffness for fibrosis assessment.

Main Methods:

• Systematic review and summarization of established HCC risk scores (IPM, CU-HCC, GAG-HCC, NGM-HCC, REACH-B, Page-B).
• Introduction of new scoring systems utilizing liver stiffness measurements (LSM) from transient elastography.
• Inclusion of models like LSM-HCC and modified REACH-B (mREACH-B) for noninvasive fibrosis assessment.

Main Results:

• Existing HCC risk scores, primarily validated in treatment-naïve Asian CHB patients, demonstrate high negative predictive values (≥95%).
• Novel models incorporating liver stiffness measurements offer noninvasive alternatives for fibrosis and HCC risk assessment.
• The study highlights a range of predictive tools, from traditional risk factors to advanced elastography-based scores.

Conclusions:

• Accurate prediction of HCC risk in CHB patients is vital for personalized management.
• A variety of validated HCC prediction models exist, with ongoing development of noninvasive tools.
• New scoring systems integrating liver stiffness show promise for improved, noninvasive risk stratification in CHB.