Improved Detection of Hepatocellular Carcinoma by Using a Longitudinal Alpha-Fetoprotein Screening Algorithm

Area of Science:

• Hepatology
• Oncology
• Medical Diagnostics

Background:

• Hepatocellular carcinoma (HCC) surveillance is crucial due to limited treatment options for advanced stages.
• The effectiveness of alpha-fetoprotein (AFP) in HCC surveillance is debated.
• Early detection of HCC is critical for reducing mortality.

Purpose of the Study:

• To enhance the sensitivity of AFP testing for HCC surveillance.
• To develop and validate a patient-specific algorithm for interpreting AFP results.
• To compare a novel screening algorithm with the traditional single threshold approach.

Main Methods:

• Analysis of de-identified data from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) trial.
• Prospective follow-up of 1050 patients with hepatitis C and advanced fibrosis or cirrhosis.
• Comparison of a parametric empirical Bayes (PEB) screening algorithm with a single threshold method for AFP interpretation.

Main Results:

• The PEB algorithm significantly improved AFP sensitivity for HCC detection in both cirrhosis (60.4% to 77.1%) and advanced fibrosis (72.5% to 87.5%) groups.
• PEB detected HCC earlier by 1.4-1.9 years compared to the single threshold approach.
• These improvements were observed with a 10% false-positive rate across all screenings.

Conclusions:

• The PEB algorithm enhances AFP test sensitivity for HCC surveillance in hepatitis C patients.
• This novel approach enables earlier detection of HCC in patients with advanced fibrosis or cirrhosis.
• Findings suggest a reevaluation of AFP and ultrasound combination in HCC surveillance protocols.