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

Abstract

Background: Surveillance for HCC remains important after hepatitis C cure. Improved sensitivity of screening with alpha-fetoprotein (AFP) by using a parametric empirical Bayes (PEB) algorithm, which incorporates an individual patient's longitudinal AFP measurements, was previously demonstrated in a retrospective analysis of clinical trial data prior to widespread hepatitis C cure.

Methods: We analyzed de-identified data extracted from the medical records of participants in the Alaska Hepatitis C Study, which aims to enroll all Alaska Native persons living in Alaska with a history of hepatitis C.We compared the performance characteristics of AFP as a screening test using the PEB method versus a fixed cutoff (FC) method in an observational setting, separately for HCC surveillance in active and cured hepatitis C.

Results: The PEB and FC methods were applied to AFP levels from participants with F3/F4 fibrosis who had active hepatitis C (173 no HCC, 14 HCC) or after they achieved hepatitis C cure (162 no HCC, 12 HCC). Compared to a fixed 20 ng/mL cutoff, demonstrating 91.2% specificity in active hepatitis C, PEB increased sensitivity from 64.3% to 71.4%. After cure, a fixed 7.2 ng/mL cutoff demonstrated 91.2% specificity, and PEB increased sensitivity from 58.3% to 91.7%.

Conclusions: The PEB algorithm can increase sensitivity and lead to earlier detection of HCC among patients with F3/F4 fibrosis, both in active and even more so in cured hepatitis C. Lower AFP levels after cure indicate that for either PEB or FC methods, screening parameters, such as cutoffs for a target specificity, should be specified separately by hepatitis C treatment status for HCC surveillance.