Surveillance Imaging and GAAD/GALAD Scores for Detection of Hepatocellular Carcinoma in Patients with Chronic Hepatitis

Early detection of hepatocellular carcinoma (HCC) is crucial for improving survival in patients with chronic hepatitis. The GALAD algorithm combines gender (biological sex), age, α-fetoprotein (AFP), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3), and protein induced by vitamin K absence or antagonist-II (PIVKA-II) for HCC detection. Similarly, the GAAD algorithm incorporates gender (biological sex), age, AFP, and PIVKA-II. This study aimed to assess the clinical utility of AFP-L3 in the GALAD algorithm and its potential synergies with ultrasound. We compared the clinical performance of GALAD with GAAD; AFP; AFP-L3; and PIVKA-II, with or without ultrasound, in Taiwanese adults.

A total of 439 serum samples were analyzed using a Cobas^® e 601 analyzer (healthy controls, n = 200; chronic liver disease controls, n = 177; HCC cases, n = 62). Performance was assessed through receiver operating characteristic curve analyses to calculate the area under the curve.

The area under the curve for differentiating early-stage HCC from patients with chronic liver disease was optimal for PIVKA-II (84.9%), GAAD (79.8%), and GALAD (79.4%), with slightly improved performance for detecting all-stage HCC. Clinical performance was unaffected by disease stage or etiology. Sensitivity for early-stage HCC was highest for GAAD (57.6%) and GALAD (57.6%). Sensitivity for each strategy was further enhanced when combined with ultrasound, regardless of disease stage or etiology (P < 0.01).

These findings indicate that the role of AFP-L3 in the GALAD algorithm is minimal, supporting the use of GAAD for HCC detection. A combination of GAAD, GALAD, or PIVKA-II with ultrasound may improve diagnostic efficiency compared with recommended strategies.