Hou Jinlin, Berg Thomas, Vogel Arndt, Piratvisuth Teerha, Trojan Jörg, De Toni Enrico N, Kudo Masatoshi, Malinowsky Katarina, Findeisen Peter, Hegel Johannes Kolja, Schöning Wenzel, Madin Kairat, Kroeniger Konstantin, Lik-Yuen Chan Henry, Sharma Ashish
Hepatology Unit and Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou China.
Division of Hepatology, Department of Medicine II, University of Leipzig Medical Center, Leipzig, Germany.
JHEP Rep. 2024 Nov 8;7(2):101263. doi: 10.1016/j.jhepr.2024.101263. eCollection 2025 Feb.
BACKGROUND & AIMS: We compared the clinical performance of the novel GAAD (gender [biological sex], age, alpha-fetoprotein [AFP], des-gamma carboxyprothrombin [DCP]) and GALAD (gender [biological sex], age, AFP, agglutinin-reactive AFP [AFP-L3], DCP) algorithms to deduce the clinical utility of AFP-L3 for detecting early-stage hepatocellular carcinoma (HCC) from chronic liver disease (CLD).
An algorithm development study (STOP-HCC-ARP) and clinical validation study (STOP-HCC-MCE) were conducted, recruiting adult participants with HCC (confirmed by radiology or pathology) or CLD in an international, multicenter, case-control design. Serum biomarkers were measured using Elecsys assays (GAAD and GALAD [Cobas]) or μTASWAKO assays (GALAD [μTASWAKO]) while blinded to case/control status.
In STOP-HCC-ARP (algorithm development cohort), 1,006 patients {297 HCC (41.4% early-stage [Barcelona Clinic Liver Cancer {BCLC} 0/A) and 709 CLD} were included. Area under the curve (AUCs) for discriminating between early-stage HCC CLD were 91.4%, 91.4%, and 90.8% for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO), respectively. The clinical validation cohort of STOP-HCC-MCE comprised 1,142 patients, (366 HCC cases [48% early-stage], 468 specificity samples and 302 CLD); AUCs for GAAD (Cobas), GALAD (Cobas), and GALAD (μTASWAKO) for discriminating between early-stage HCC CLD were 91.4%, 91.5%, and 91.0%, respectively; AUCs were 94.7-95.0% for all-stage HCC. The GAAD and GALAD algorithms demonstrated similar good performance regardless of disease etiology, presence of cirrhosis, geographical region, and within pan-tumor specificity panels ( <0.001).
GAAD (Cobas) demonstrated good clinical performance, similar to GALAD (Cobas and μTASWAKO) algorithms, in differentiating HCC and CLD controls, across all disease stages, etiologies, and regions; therefore, AFP-L3 may have a negligible role in GALAD for HCC surveillance.
To improve the detection of early-stage hepatocellular carcinoma (HCC) from benign chronic liver disease (CLD), algorithms combining demographic characteristics and serum biomarkers, such as GAAD and GALAD, have been developed. GAAD combines gender (biological sex), age, alpha-fetoprotein (AFP), des-gamma carboxy-prothrombin (DCP); GALAD combines the same characteristics and biomarkers as GAAD with the addition of agglutinin-reactive AFP (AFP-L3). Changing disease etiologies and treatment paradigms have raised questions regarding the utility of AFP-L3 in HCC surveillance. Our work demonstrates that the GAAD (Cobas) algorithm demonstrated good clinical performance and was as sensitive and specific as the GALAD (Cobas) and GALAD (μTASWAKO) algorithms in differentiating HCC and CLD controls, across all disease stages, etiologies, and geographical regions; therefore, AFP-L3 may have a negligible role in HCC detection. Our study provides supporting evidence that in participants with CLD undergoing guideline-directed HCC surveillance, the GAAD (Cobas) algorithm may be used as an effective method for the detection of HCC, potentially resulting in improved patient outcomes.
我们比较了新型GAAD（性别[生理性别]、年龄、甲胎蛋白[AFP]、异常凝血酶原[DCP]）和GALAD（性别[生理性别]、年龄、AFP、凝集素反应性AFP[AFP-L3]、DCP）算法的临床性能，以推断AFP-L3在从慢性肝病（CLD）中检测早期肝细胞癌（HCC）方面的临床效用。
进行了一项算法开发研究（STOP-HCC-ARP）和临床验证研究（STOP-HCC-MCE），采用国际多中心病例对照设计招募患有HCC（经放射学或病理学确诊）或CLD的成年参与者。在对病例/对照状态不知情的情况下，使用电化学发光免疫分析法（GAAD和GALAD[ Cobas]）或μTASWAKO分析法（GALAD[μTASWAKO]）检测血清生物标志物。
在STOP-HCC-ARP（算法开发队列）中，纳入了1006例患者{297例HCC（41.4%为早期[巴塞罗那临床肝癌{BCLC}0/A期]）和709例CLD}。GAAD（Cobas）、GALAD（Cobas）和GALAD（μTASWAKO）区分早期HCC和CLD的曲线下面积（AUC）分别为91.4%、91.4%和90.8%。STOP-HCC-MCE的临床验证队列包括1142例患者（366例HCC病例[48%为早期]、468例特异性样本和302例CLD）；GAAD（Cobas）、GALAD（Cobas）和GALAD（μTASWAKO）区分早期HCC和CLD的AUC分别为91.4%、91.5%和91.0%；区分所有阶段HCC的AUC为94.7 - 95.0%。无论疾病病因、肝硬化的存在、地理区域以及在泛肿瘤特异性检测组内，GAAD和GALAD算法均表现出相似的良好性能（P<0.001）。
在区分所有疾病阶段、病因和区域的HCC与CLD对照方面，GAAD（Cobas）表现出良好的临床性能，与GALAD（Cobas和μTASWAKO）算法相似；因此，AFP-L3在GALAD用于HCC监测中的作用可能微不足道。
为了提高从良性慢性肝病（CLD）中检测早期肝细胞癌（HCC）的能力，已经开发了结合人口统计学特征和血清生物标志物的算法，如GAAD和GALAD。GAAD结合了性别（生理性别）、年龄、甲胎蛋白（AFP）、异常凝血酶原（DCP）；GALAD在GAAD的相同特征和生物标志物基础上增加了凝集素反应性AFP（AFP-L3）。不断变化的疾病病因和治疗模式引发了关于AFP-L3在HCC监测中效用的问题。我们的研究表明，GAAD（Cobas）算法表现出良好的临床性能，在区分所有疾病阶段、病因和地理区域的HCC与CLD对照方面与GALAD（Cobas）和GALAD（μTASWAKO）算法一样敏感和特异；因此，AFP-L3在HCC检测中的作用可能微不足道。我们的研究提供了支持性证据，即在接受指南指导的HCC监测的CLD参与者中，GAAD（Cobas）算法可作为检测HCC的有效方法，可能改善患者预后。
