ArticleClinical and molecular hepatology2026
GAFAD: A liquid chromatography-tandem mass spectrometry-based model for early hepatocellular carcinoma detection beyond GALAD's limitations.
Article in Clinical and molecular hepatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
BACKGROUND/
aimsThe GALAD (Gender, Age, Lens culinaris agglutinin-reactive alpha-fetoprotein [AFP-L3], alpha-fetoprotein [AFP], and des-γ-carboxy prothrombin) 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. Furthermore, the lectin-based AFP-L3 assay has poor sensitivity at low AFP concentrations, limiting detection of small or AFP-negative tumors.
methodsWe developed GAFAD, a multivariable model replacing AFP-L3 with fucosylated AFP percentage, quantified by a validated liquid chromatography-tandem mass spectrometry 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.
resultsIn 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.
conclusionsGAFAD 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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