HCC surveillance in hepatitis C: A longitudinal algorithm improves alpha-fetoprotein screening.

Area of Science:

• Hepatology
• Oncology
• Biostatistics

Background:

• Hepatocellular carcinoma (HCC) surveillance is crucial even after hepatitis C cure.
• Alpha-fetoprotein (AFP) screening sensitivity can be improved using advanced algorithms.
• Previous studies showed promise for the parametric empirical Bayes (PEB) algorithm in retrospective analyses.

Purpose of the Study:

• To compare the performance of the PEB algorithm versus a fixed cutoff (FC) method for HCC surveillance.
• To evaluate AFP screening effectiveness in active and cured hepatitis C patients.
• To assess the utility of PEB for early HCC detection in individuals with F3/F4 fibrosis.

Main Methods:

• Analysis of de-identified data from the Alaska Hepatitis C Study.
• Comparison of PEB and FC methods for AFP screening in an observational setting.
• Separate analysis for HCC surveillance in active and cured hepatitis C cohorts.

Main Results:

• PEB increased sensitivity for HCC detection compared to FC in both active (71.4% vs 64.3%) and cured (91.7% vs 58.3%) hepatitis C patients.
• Specificity remained high for both methods (91.2%) in active hepatitis C.
• PEB demonstrated a substantial sensitivity increase after hepatitis C cure.

Conclusions:

• The PEB algorithm enhances HCC detection sensitivity, enabling earlier diagnosis in patients with F3/F4 fibrosis.
• The algorithm is particularly effective for HCC surveillance in patients who have been cured of hepatitis C.
• Screening parameters, including AFP cutoffs, should be tailored to hepatitis C treatment status for optimal HCC surveillance.