Development of a novel diagnostic model integrating microRNAs and GALAD for HBV-related hepatocellular carcinoma.

AIMS: As primary hepatocellular carcinoma (HCC) is a prevalent digestive tract malignancy, identifying novel biomarkers for early diagnosis and prognosis is crucial. This study combined specific miRNAs with the GALAD model to create a new diagnostic model for hepatitis B virus (HBV)-related HCC. PATIENTS & METHODS: From 2020 to 2022, 884 patients from Zhongshan Hospital were enrolled, including 430 HBV-related HCC, 275 HBV-related chronic liver disease (CLD), and 179 healthy donors (HD). Stepwise regression selected features, and multivariable logistic regression built the GALADM model. A nomogram integrating age, gender, serum markers, and a score derived from seven plasma cell-free microRNAs (miRNA7) was developed. RESULTS: MiRNA7 value was higher in HCC patients and rose with disease progression. The GALADM model showed superior diagnostic performance, with AUCs of 0.87, 0.96, and 0.90 when distinguishing HCC from CLD, HD, and CLD+HD, outperforming the GALAD model and single markers. It also excelled in diagnosing early-stage and Alpha-fetoprotein (AFP)-negative HCC. The nomogram had an AUC of 0.977 and proved clinically useful. CONCLUSION: The GALADM model, combining miRNA7 with the GALAD model, surpasses the original GALAD model, enabling early-stage and AFP-negative HCC diagnosis.