Validation of the GALAD model for diagnosing HBV-related hepatocellular carcinoma in Chinese patients

Area of Science:

• Hepatology
• Oncology
• Biomarker Research

Background:

• Hepatocellular Carcinoma (HCC) diagnosis relies on models like GALAD, integrating serological biomarkers (AFP, AFP-L3%, DCP) and demographics.
• The utility of the GALAD model in Chinese populations with Hepatitis B Virus (HBV)-related HCC requires further validation.

Purpose of the Study:

• To validate the clinical utility and diagnostic performance of the GALAD model in a Chinese population with HBV-related HCC.
• To compare the diagnostic accuracy of the GALAD model against individual serological biomarkers.

Main Methods:

• A retrospective cohort study included 217 HBV-related HCC patients, 210 benign liver disease patients, 247 cirrhosis patients, and 220 healthy controls.
• Serum levels of AFP, AFP-L3%, and DCP were measured, and Receiver Operating Characteristic (ROC) curve analysis was used to assess diagnostic performance.
• Model calibration was evaluated using the Hosmer-Lemeshow test.

Main Results:

• The GALAD model achieved a high diagnostic performance with an Area Under the Curve (AUC) of 0.942.
• At an optimal cutoff of 1.89, the model demonstrated 89.91% sensitivity and 81.51% specificity.
• The model exhibited excellent calibration (χ² = 8.934, p > 0.05), indicating its reliability for the target population.

Conclusions:

• The GALAD model significantly outperforms individual biomarkers for diagnosing HBV-related HCC in Chinese patients.
• The GALAD model is a reliable, cost-effective tool with potential for clinical application, particularly in tertiary prevention for HBV-related HCC in resource-limited settings.