GAFAD：GALADの限界を超えた早期肝細胞がん検出のためのLC-MS/MSベースモデル

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.

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.

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.

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