Improving the Early Detection of Hepatocellular Carcinoma in Patients with Chronic Liver Disease: An Integrated C-GALAD Model and Cell-Free DNA Approach.

Abstract

Background/Aims Chronic liver disease (CLD) confers an increased risk of hepatocellular carcinoma (HCC), but individual biomarkers have limited diagnostic performance, necessitating a combined approach. The study aimed to evaluate the value of a combined strategy integrating the C-GALAD (gender, age, lens culinaris agglutinin-reactive alpha fetoprotein [AFP-L3], and des-gamma-carboxy prothrombin [DCP]) model with circulating cell-free DNA (cfDNA) for the early detection of progression from CLD to HCC. Materials and Methods A total of 226 patients (HCC, n = 57; CLD without HCC, n = 169) were enrolled. Pretreatment blood samples were collected, and AFP, AFP-L3, and DCP levels were measured; C-GALAD scores were calculated. Plasma cfDNA was extracted and quantified. Baseline clinical characteristics (age, sex, etiology, and cirrhosis) and laboratory parameters (platelet count, total bilirubin, serum albumin [ALB], AFP, AFP-L3, and DCP) were compared between groups. Multivariate logistic regression and receiver operating characteristic curve analysis were performed to identify independent diagnostic factors and evaluated diagnostic performance. Results The HCC group had a higher prevalence of cirrhosis, lower ALB levels, and higher AFP, AFP-L3, and DCP levels than the CLD group. Median C-GALAD scores were 51 (interquartile range [IQR], 43-57) in the HCC group and 51 (IQR, 46-58) in the CLD group, whereas cfDNA concentrations were 40.25 (IQR, 33.41-48.19) and 31.62 (25.90-35.45) ng/mL, respectively (both P < .001). Multivariable logistic regression identified cirrhosis (adjusted odds ratio [OR], 3.14; 95% CI, 1.18-8.37; P = .022), C-GALAD score (adjusted OR, 2.32; 95% CI, 1.73-3.10; P < .001), and cfDNA concentration (adjusted OR, 1.20; 95% CI, 1.12 1.30; P < .001) as independent predictors of HCC. The area under the curve (AUC) was 0.850 for C-GALAD (sensitivity, 66.67%; specificity, 89.94%) and 0.799 for cfDNA. The combined model achieved an AUC of 0.917, with a sensitivity of 82.46%, specificity of 91.72%, accuracy of 89.38%, positive predictive value of 77.05%, and negative predictive value of 93.94%. Conclusion The combined C-GALAD and cfDNA strategy significantly improves the accuracy of early HCC detection in patients with CLD, demonstrating excellent diagnostic performance.