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씨젠의료재단

Clin. Mol. Hepatol., Feb 25 2026, | https://doi.org/10.3350/cmh.2025.1244 GAFAD: An LC-MS/MS-Based Model for Early Hepatocellular Carcinoma Detection Beyond GALAD's Limitation

Hyojin Kim ¹, Wonseok Oh ¹, Juri Park ¹, Saeyoung Lee ¹, Won Suk Yang ¹, Soon Sun Kim ², Jae Youn Cheong ², Je-Hyun Baek 1 *

¹R&D Center for Clinical Mass Spectrometry, Seegene Medical Foundation, Seoul, Republic of Korea.
²Department of Gastroenterology, Ajou University School of Medicine, Suwon, Republic of Korea.

^*Corresponding author: correspondence to Je-Hyun Baek

Abstract

Background/Aims
The GALAD (Gender, Age, Lens culinaris agglutinin-reactive alpha-fetoprotein [AFP-L3], alpha-fetoprotein [AFP], and des-γ-carboxy prothrombin [DCP]) score, widely used for hepatocellular carcinoma (HCC) detection, was primarily derived from cohorts with advanced-stage tumors and elevated biomarker levels, potentially overestimating accuracy in early-stage disease. Furthemore, the lectin-based AFP-L3 assay has poor sensitivity at low AFP concentrations, limiting detection of small or AFP-negative tumors.

Methods
We developed GAFAD, a multivariable model replacing AFP-L3 with fucosylated AFP percentage (AFP-Fuc%), quantified by a validated liquid chromatography–tandem mass spectrometry (LC-MS/MS) assay. The model was trained and tested using a hepatitis B virus (HBV)-related cohort (HCC n=235; non-HCC n=290), a diagnostically challenging set with substantial overlap in biomarker levels between HCC and non-HCC. Moreover, a final model (GAFAD) was validated in two independent cohorts (HCC n=210, non-HCC n=245), comprising HBV-, HCV-related and non-viral etiologies.

Results
In the development cohort, GAFAD showed superior diagnostic performance to GALAD for distinguishing HCC from non-HCC, with a higher area under the receiver operating characteristic curve (AUC, 0.938 vs. 0.887; p<0.0001) and greater sensitivity (82% vs. 66%) and accuracy (86% vs. 79%) at 90% specificity. In the external validation cohort, GAFAD similarly outperformed GALAD, achieving a higher AUC (0.874 vs. 0.841, p<0.05), greater sensitivity (72% vs. 57%), and improved accuracy (82% vs. 75%) at 90% specificity. This superiority extended to early-stage, very-early-stage, and AFP-negative HCC.

Conclusions
GAFAD provides a reliable and generalizable tool for early HCC detection across diverse etiologies, supporting its clinical applicability in surveillance and diagnosis.

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