Comparative evaluation of multimarker algorithms for early-stage HCC detection in multicenter prospective studies.

Area of Science:

• Hepatology
• Oncology
• Biomarker Discovery

Background:

• Hepatocellular carcinoma (HCC) detection relies on algorithms combining demographic data and serum biomarkers.
• The GAAD algorithm includes gender, age, AFP, and DCP, while GALAD adds AFP-L3.
• The clinical utility of AFP-L3 in HCC surveillance requires re-evaluation due to changing disease patterns.

Purpose of the Study:

• To compare the clinical performance of GAAD and GALAD algorithms for early-stage HCC detection.
• To determine the clinical utility of AFP-L3 in differentiating HCC from chronic liver disease (CLD).

Main Methods:

• Algorithm development (STOP-HCC-ARP) and validation (STOP-HCC-MCE) studies were conducted.
• International, multicenter, case-control design included participants with HCC or CLD.
• Serum biomarkers were measured using Elecsys and μTASWAKO assays.

Main Results:

• In the development cohort (n=1006), AUCs for early-stage HCC vs. CLD were similar for GAAD (Cobas) and GALAD (Cobas/μTASWAKO) at ~91%.
• In the validation cohort (n=1142), AUCs for early-stage HCC vs. CLD were ~91.4% for GAAD (Cobas) and GALAD (Cobas/μTASWAKO).
• All-stage HCC detection showed AUCs of 94.7-95.0%; performance was consistent across etiologies, cirrhosis presence, and regions.

Conclusions:

• The GAAD (Cobas) algorithm demonstrated comparable clinical performance to GALAD (Cobas/μTASWAKO) in differentiating HCC from CLD.
• AFP-L3 appears to have a negligible role in the GALAD algorithm for HCC surveillance.
• GAAD (Cobas) may serve as an effective tool for HCC detection in patients with CLD undergoing surveillance.