Demirtas Coskun O, Akin Sehnaz, Yilmaz Karadag Demet, Yilmaz Tuba, Ciftci Ugur, Huseynov Javid, Tolu Bulte Tugba, Armutcuoglu Kaldirim Yasemin, Dilber Feyza, Ozdogan Osman Cavit, Eren Fatih
Division of Gastroenterology and Hepatology, Marmara University School of Medicine, Istanbul 34854, Türkiye.
Institute of Gastroenterology, Marmara University School of Medicine, Istanbul 34854, Türkiye.
Cancers (Basel). 2025 Jul 18;17(14):2390. doi: 10.3390/cancers17142390.
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. : 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. : 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). : 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.
诸如晶状体凝集素反应性甲胎蛋白和去γ-羧基凝血酶原等生物标志物,以及基于生物标志物和/或临床参数的复合模型(GALAD、GAAP、ASAP、aMAP、多伊尔斯顿模型),除甲胎蛋白外可能会改善检测效果,但不同人群的比较数据仍然有限。在这项基于生物样本库的病例对照研究中,我们在2019年1月至2024年期间评估了562名成年人(120名健康对照者、277名慢性肝病患者、165名肝细胞癌患者)。在三个阈值下评估了任何阶段和早期肝细胞癌的诊断性能:约登指数得出的最佳临界值、研究确定的临界值以及确保90%特异性的临界值。进行了受试者操作特征分析。亚组分析按病因和甲胎蛋白状态分层。在最佳临界值时,GALAD对任何阶段(90.3%)和早期(89.1%)肝细胞癌显示出最高敏感性,特异性为70 - 80%。使用既定临界值时,GALAD对任何阶段(75.8%)和早期(57.8%)肝细胞癌保持最高敏感性,特异性为93.5%。GALAD在非病毒性肝细胞癌中表现最佳(曲线下面积为0.872),而GAAP和ASAP在病毒病因方面显示出类似的高曲线下面积值(曲线下面积为0.955 - 0.960)。我们的结果证明了GALAD评分在不同人群中的一致性能,并强调了其相对于单个生物标志物和其他复合模型的优越性。值得注意的是,GAAP和ASAP评分(少使用一种生物标志物(甲胎蛋白异质体L3))表现出可比的性能,特别是在病毒病因方面。这些发现支持将复合生物标志物模型纳入量身定制的肝细胞癌监测策略。