Performance of the GALAD Model in an Asian Cohort Undergoing Hepatocellular Carcinoma Surveillance: A Prospective Cohort Study.

Abstract

Background and aim: Current hepatocellular carcinoma (HCC) surveillance strategy has its limitations, consequently delaying early detection. The GALAD model has been validated in retrospective studies, with two published cut-off values yielding different sensitivities for HCCs of different etiologies. We evaluated the performance of GALAD model in HCC surveillance and determined the ideal cut-off value for our cohort.

Methods: Patients undergoing 6-monthly HCC surveillance in Singapore General Hospital were recruited between December 2017-October 2018. Study serum specimens were prospectively collected and retrospectively tested using the μTASWako alpha-fetoprotein (AFP), AFP-L3, and protein induced by vitamin K antagonism-II (PIVKA-II) kits. GALAD score was calculated and compared with individual biomarkers using area under the curve (AUC) analysis. Published GALAD cut-offs of -0.63 and -1.95 were compared for their performance in HCC detection.

Results: There were 207 patients (median age 59 years, 55.1% males). Hepatitis B was the commonest etiology (72.9%). By February 2023, with a median follow-up of 48.9 months, 20 patients had developed HCC. Eight patients developed HCC within 1 year from specimen collection. For HCC developing within 1 year, GALAD model detected HCC with an AUC of 0.84, greater than AFP (AUC 0.77), AFP-L3 (AUC 0.60), and PIVKA-II (AUC 0.67). GALAD at cut-off -1.95 achieved sensitivity and specificity of 75% and 92.5% for HCCs detected within 1 year, superior to cut-off -0.63 (sensitivity 12.5%, specificity 100%).

Conclusion: In this prospective study of HCC surveillance, the GALAD model performed better than individual biomarkers. The cut-off of -1.95 was more useful in our predominantly chronic hepatitis B cohort.