Enhancing Hepatocellular Carcinoma Surveillance: Comparative Evaluation of AFP, AFP-L3, DCP and Composite Models in a Biobank-Based Case-Control Study

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Background/Objectives: Biomarkers such as lens agglutinin-reactive alpha-fetoprotein and des-gamma-carboxy prothrombin, as well as biomarker- and/or clinical-parameter-derived composite models (GALAD, GAAP, ASAP, aMAP, Doylestown), may improve detection in addition to alpha-fetoprotein, yet comparative data across diverse populations remain limited. Methods: In this biobank-based case–control study, we evaluated 562 adults (120 healthy controls, 277 chronic liver disease, 165 hepatocellular carcinoma) from January 2019 to 2024. Diagnostic performance for any-stage and early-stage hepatocellular carcinoma was assessed across three thresholds: Youden-index-derived optimal cut-offs, research-established cut-offs, and cut-offs ensuring 90% specificity. Receiver operating characteristic analysis was performed. Subgroup analyses were stratified by etiology and alpha-fetoprotein status. Results: At optimal cut-offs, GALAD showed the highest sensitivity for any-stage (90.3%) and early-stage (89.1%) hepatocellular carcinoma, with 70–80% specificity. Using established cut-offs, GALAD retained the highest sensitivity for any-stage (75.8%) and early-stage (57.8%) hepatocellular carcinoma, with 93.5% specificity. GALAD demonstrated the best performance in non-viral hepatocellular carcinomas (area under the curve 0.872), whereas GAAP and ASAP showed similarly high area under the curve values in viral etiology (area under the curve 0.955–0.960). Conclusions: Our results demonstrate the consistent performance of the GALAD score across diverse populations and underscore its superiority over individual biomarkers and other composite models. Notably, the GAAP and ASAP scores—which use one less biomarker (AFP-L3)—exhibited comparable performance, particularly in viral etiology. These findings support the integration of the composite biomarker models into tailored hepatocellular carcinoma surveillance strategies.