Predictive models for hepatocellular carcinoma development after sustained virological response in advanced hepatitis...

Area of Science:

• Hepatology
• Oncology
• Virology

Background:

• Hepatocellular carcinoma (HCC) surveillance is recommended for patients with advanced hepatitis C after sustained virological response (SVR).
• Identifying patients who can safely discontinue surveillance is crucial for resource optimization.
• This study focuses on patients with advanced, compensated fibrosis (≥F3) who achieved SVR with interferon-free therapies.

Purpose of the Study:

• To identify subsets of patients with advanced hepatitis C who have a low risk of developing hepatocellular carcinoma (HCC) after achieving sustained virological response (SVR).
• To develop predictive models for HCC risk stratification using non-invasive markers.

Main Methods:

• Prospective follow-up of 491 patients with advanced fibrosis (≥F3) who achieved SVR.
• Collection of clinical-biological parameters and liver stiffness measurement (LSM) before treatment (ST) and at SVR.
• Development of two predictive models (Model-A: LSM-based; Model-B: FIB-4 score-based) using SVR parameters for HCC risk stratification.

Main Results:

• During a median follow-up of 49.8 months, 29 patients (5.9%) developed HCC (incidence rate: 1.6/100 patient-years).
• Model-A identified independent predictors: LSM, age, and albumin. Model-B identified: FIB-4 score and albumin.
• Both models successfully stratified patients, identifying low-risk groups with HCC incidence rates of 0.16/100 PYs (Model-A) and 0.25/100 PYs (Model-B).

Conclusions:

• Simple, non-invasive models utilizing LSM or FIB-4, age, and albumin at SVR can identify patients with a very low HCC risk (<1%/year).
• These models facilitate the identification of patient subsets for whom HCC surveillance may not be cost-effective.
• Refined HCC surveillance strategies can be implemented based on these risk stratification tools.