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

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) has limited treatment options when diagnosed at advanced stages; therefore, early detection is critical to reduce mortality. There is disagreement about the value of α-fetoprotein (AFP) in HCC surveillance. We aim to improve the sensitivity of AFP in HCC surveillance by using an algorithm that incorporates screening history to define patient-specific thresholds for positive a screen. METHODS: De-identified data from the Hepatitis C Antiviral Long-term Treatment against Cirrhosis (HALT-C) trial, which enrolled 1050 patients with hepatitis C and advanced fibrosis or cirrhosis who were prospectively followed every 3-6 months, were analyzed. AFP was assayed at each visit, and ultrasonography was performed every 6-12 months. A panel adjudicated the diagnosis of HCC. A parametric empirical Bayes (PEB) screening algorithm, which incorporates screening history, was compared with a single threshold approach for interpreting AFP results. RESULTS: During a median follow-up of 80 months, 88 patients (48 of 427 with cirrhosis and 40 of 621 with advanced fibrosis) were diagnosed with HCC. PEB improved the sensitivity of AFP for detecting all HCC from 60.4% to 77.1% (P < .0005) in patients with cirrhosis and from 72.5% to 87.5% (P = .0015) in patients with advanced fibrosis, when the false-positive rate among all screenings was set at 10%. PEB algorithm detected HCC 1.7-1.9 years earlier in the cirrhosis group and 1.4-1.7 years earlier in the advanced fibrosis group, compared with single threshold approach. CONCLUSIONS: PEB increases the sensitivity of AFP testing and detects HCC earlier among hepatitis C patients with advanced fibrosis or cirrhosis. These data should prompt a reevaluation of how AFP is used in combination with ultrasound in HCC surveillance.