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. 2024 Nov 28;12(11):907-916.
doi: 10.14218/JCTH.2024.00172. Epub 2024 Oct 14.

Surveillance Imaging and GAAD/GALAD Scores for Detection of Hepatocellular Carcinoma in Patients with Chronic Hepatitis

Chung-Feng Huang  1   2   3 , Konstantin Kroeniger  4 , Chih-Wen Wang  1   3   5 , Tyng-Yuan Jang  1   3 , Ming-Lun Yeh  1   3 , Po-Cheng Liang  1 , Yu-Ju Wei  1   6 , Po-Yao Hsu  1 , Ching-I Huang  1   3 , Ming-Yen Hsieh  1   6 , Yi-Hung Lin  1   5 , Jee-Fu Huang  1   3 , Chia-Yen Dai  1   3 , Wan-Long Chuang  1   3 , Ashish Sharma  7 , Ming-Lung Yu  1   3   8
Affiliations

Surveillance Imaging and GAAD/GALAD Scores for Detection of Hepatocellular Carcinoma in Patients with Chronic Hepatitis

Chung-Feng Huang et al. J Clin Transl Hepatol. .

Abstract

Background and aims: Early detection of hepatocellular carcinoma (HCC) is crucial for improving survival in patients with chronic hepatitis. The GALAD algorithm combines gender (biological sex), age, α-fetoprotein (AFP), Lens culinaris agglutinin-reactive fraction of AFP (AFP-L3), and protein induced by vitamin K absence or antagonist-II (PIVKA-II) for HCC detection. Similarly, the GAAD algorithm incorporates gender (biological sex), age, AFP, and PIVKA-II. This study aimed to assess the clinical utility of AFP-L3 in the GALAD algorithm and its potential synergies with ultrasound. We compared the clinical performance of GALAD with GAAD; AFP; AFP-L3; and PIVKA-II, with or without ultrasound, in Taiwanese adults.

Methods: A total of 439 serum samples were analyzed using a Cobas® e 601 analyzer (healthy controls, n = 200; chronic liver disease controls, n = 177; HCC cases, n = 62). Performance was assessed through receiver operating characteristic curve analyses to calculate the area under the curve.

Results: The area under the curve for differentiating early-stage HCC from patients with chronic liver disease was optimal for PIVKA-II (84.9%), GAAD (79.8%), and GALAD (79.4%), with slightly improved performance for detecting all-stage HCC. Clinical performance was unaffected by disease stage or etiology. Sensitivity for early-stage HCC was highest for GAAD (57.6%) and GALAD (57.6%). Sensitivity for each strategy was further enhanced when combined with ultrasound, regardless of disease stage or etiology (P < 0.01).

Conclusions: These findings indicate that the role of AFP-L3 in the GALAD algorithm is minimal, supporting the use of GAAD for HCC detection. A combination of GAAD, GALAD, or PIVKA-II with ultrasound may improve diagnostic efficiency compared with recommended strategies.

Keywords: Algorithm; Biomarkers; Cirrhosis; Detection; Diagnosis; GAAD; GALAD; Hepatocellular carcinoma; Liver cancer; Surveillance; Ultrasound.

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Conflict of interest statement

WLC: Member of advisory boards for Gilead, AbbVie, Vaccitech, PharmaEssentia; speaker for Gilead, AbbVie, BMS, Roche, and has been an Editorial Board Member of Journal of Clinical and Translational Hepatology since 2022. CFH: Speaker for AbbVie, BMS, Gilead, Merck, and Roche, JFH: Consultant for Roche, Gilead, Sysmex, and Aligos; speaker for AbbVie, Gilead, and Sysmex; and has been an Editorial Board Member of Journal of Clinical and Translational Hepatology since 2022. MLYu: Research grants from AbbVie, Gilead, Merck, and Roche Diagnostics; consultant for AbbVie, BMS, Gilead, Roche, and Roche Diagnostics; and speaker for AbbVie, BMS, Eisai, Gilead, Roche, and Roche Diagnostics; and has been an Associate Editor of Journal of Clinical and Translational Hepatology since 2023. AS is an employee of Roche Diagnostics International AG. KK is an employee of Roche Diagnostics GmbH. MLYeh has been an Editorial Board Member of Journal of Clinical and Translational Hepatology since 2022. The other authors have no conflict of interests related to this publication.

Figures

Fig. 1
Fig. 1. Study design and sample disposition.
CLD, chronic liver disease; HCC, hepatocellular carcinoma.
Fig. 2
Fig. 2. Distribution of GAAD and GALAD scores by (A) healthy and CLD controls, CLD controls, and HCC; (B) BCLC stage; and (C) etiology.
AFP, α-fetoprotein; AFP-L3, Lens culinaris agglutinin-reactive fraction of α-fetoprotein; PIVKA-II, protein induced by vitamin K absence or antagonist II; BCLC, Barcelona Clinic Liver Cancer; CLD, chronic liver disease; GAAD, gender (biological sex), age, AFP, PIVKA-II (previously DCP); GALAD, gender (biological sex), age, AFP-L3, AFP, PIVKA-II (previously DCP); HBV, hepatitis B virus; HCC, hepatocellular carcinoma; HCV, hepatitis C virus.
Fig. 3
Fig. 3. Receiver operating characteristic plots of GAAD and GALAD algorithms (Cobas) and Elecsys AFP, AFP-L3, and PIVKA-II assays for discriminating between early- (A) and all-stage (B) HCC patients and CLD controls.
*P < 0.0001 vs. GAAD; †P < 0.0001 vs. GALAD. P-values for comparisons between other surveillance strategies were non-significant. AFP, α-fetoprotein; AFP-L3, Lens culinaris agglutinin-reactive fraction of α-fetoprotein; AUC, area under the curve; CLD, chronic liver disease; GAAD, gender (biological sex), age, AFP, PIVKA-II; GALAD, gender (biological sex), age, AFP-L3, AFP, PIVKA-II; HCC, hepatocellular carcinoma; PIVKA-II, protein induced by vitamin K absence or antagonist II.
Fig. 4
Fig. 4. Receiver operating characteristic plots of GAAD and GALAD (Cobas) algorithms and Elecsys AFP, AFP-L3, and PIVKA-II assays for differentiation of cirrhotic CLD controls and early-stage (A) or all-stage (B) HCC patients, differentiation of non-cirrhotic CLD controls and early-stage (C) or all-stage (D) HCC patients, differentiation of CLD controls and early-stage (E) or all-stage (F) HCC patients with HBV, and differentiation of CLD controls and early-stage (G) or all-stage (H) HCV etiologies.
*P < 0.0001 vs. GAAD; †P < 0.0001 vs. GALAD. P-values for comparisons between other surveillance strategies were non-significant. AFP, α-fetoprotein; AFP-L3, Lens culinaris agglutinin-reactive fraction of α-fetoprotein; AUC, area under the curve; CLD, chronic liver disease; GAAD, gender (biological sex), age, AFP, PIVKA-II; GALAD, gender (biological sex), age, AFP-L3, AFP, PIVKA-II; HBV, hepatitis B virus; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; PIVKA-II, protein induced by vitamin K absence or antagonist II.
Fig. 5
Fig. 5. Sensitivity of US, GAAD, and GALAD (Cobas) algorithms and Elecsys AFP, AFP-L3, and PIVKA-II assays for discriminating between early-stage (A) and all-stage (B) HCC patients and controls by etiology.
*Sensitivity of the assay/algorithm when combined with ultrasound. AFP, α-fetoprotein; AFP-L3, Lens culinaris agglutinin-reactive fraction of α-fetoprotein; GAAD, gender (biological sex), age, AFP, PIVKA-II; GALAD, gender (biological sex), age, AFP-L3, AFP, PIVKA-II; HBV, hepatitis B virus; HCC, hepatocellular carcinoma; HCV, hepatitis C virus; PIVKA-II, protein induced by vitamin K absence or antagonist II; US, ultrasound.
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