Objective:To investigate the efficacy of fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), aspartate aminotransferase to platelet count ratio (APRI), liver stiffness value (LSM), and Agile 3+ score and their combined model in predicting advanced-stage liver fibrosis in patients with chronic hepatitis B (CHB) combined with metabolic-associated fatty liver disease (MAFLD).Methods:A multicenter retrospective cohort study was conducted on the BMOVE population.Nine hundred twenty CHB cases combined with MAFLD who underwent liver biopsy at seven medical centers in China from April 2006 to December 2023 were included. The patients were divided into advanced-stage liver fibrosis (159 cases) and non-advanced-stage liver fibrosis (761 cases) according to the Scheuer's scoring system.The area under the receiver operating characteristic curve (AUROC), decision curve, and calibration curve analysis were used to evaluate the efficacy of the firbrosis-4 index (FIB-4) score, NFS score, APRI index, LSM, and Agile 3+ score and their combined model in predicting advanced-stage fibrosis. The liver fibrosis grade of all patients was diagnosed by liver biopsy. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each scoring model and combined model, as well as the proportion of correctly classified patients, were calculated based on different cutoff values.Results:AUROC analysis showed that Agile 3+ (0.814, 95% CI: 0.787-0.838) and LSM (0.805, 95% CI: 0.778-0.829) had similar accuracy and were superior to FIB-4 (0.721, 95% CI: 0.691-0.749), NFS (0.687, 95% CI: 0.656-0.716) and APRI ( 0.689, 95% CI: 0.658-0.718); however, HBV DNA level and HBV e antigen status had no effect on this outcome. Decision curve analysis showed that interventions based on LSM and Agile 3+ had provided higher net benefits compared with serological scores. Calibration curves showed that Agile 3+ had better predicitive accuracy than all other models. Agile 3+ had the highest PPV (0.54), minimal uncertainty interval (11.6%), and the highest proportion of correctly classified patients (76%); followed by LSM (PPV: 0.43, uncertainty interval: 15.5%, correct classification rate: 66%), and FIB-4 (PPV: 0.42, uncertainty interval: 26.1%, correct classification rate: 62.6%) in terms of identifying advanced-stage liver fibrosis. Combined model analysis demonstrated that FIB-4 combined with Agile 3+ had improved the correct classification rate and reduced the proportion of missed patients compared with FIB-4 combined with LSM. Conclusion:The Agile 3+ score is superior than LSM, FIB-4, NFS, and APRI index at identifying advanced-stage fibrosis in patients with CHB combined with MAFLD. This study supports the use of FIB-4 index combined with Agile 3+ for risk stratification in patients with CHB combined with MAFLD.

Objective:To investigate the efficacy of fibrosis-4 index (FIB-4), NAFLD fibrosis score (NFS), aspartate aminotransferase to platelet count ratio (APRI), liver stiffness value (LSM), and Agile 3+ score and their combined model in predicting advanced-stage liver fibrosis in patients with chronic hepatitis B (CHB) combined with metabolic-associated fatty liver disease (MAFLD).Methods:A multicenter retrospective cohort study was conducted on the BMOVE population.Nine hundred twenty CHB cases combined with MAFLD who underwent liver biopsy at seven medical centers in China from April 2006 to December 2023 were included. The patients were divided into advanced-stage liver fibrosis (159 cases) and non-advanced-stage liver fibrosis (761 cases) according to the Scheuer's scoring system.The area under the receiver operating characteristic curve (AUROC), decision curve, and calibration curve analysis were used to evaluate the efficacy of the firbrosis-4 index (FIB-4) score, NFS score, APRI index, LSM, and Agile 3+ score and their combined model in predicting advanced-stage fibrosis. The liver fibrosis grade of all patients was diagnosed by liver biopsy. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of each scoring model and combined model, as well as the proportion of correctly classified patients, were calculated based on different cutoff values.Results:AUROC analysis showed that Agile 3+ (0.814, 95% CI: 0.787-0.838) and LSM (0.805, 95% CI: 0.778-0.829) had similar accuracy and were superior to FIB-4 (0.721, 95% CI: 0.691-0.749), NFS (0.687, 95% CI: 0.656-0.716) and APRI ( 0.689, 95% CI: 0.658-0.718); however, HBV DNA level and HBV e antigen status had no effect on this outcome. Decision curve analysis showed that interventions based on LSM and Agile 3+ had provided higher net benefits compared with serological scores. Calibration curves showed that Agile 3+ had better predicitive accuracy than all other models. Agile 3+ had the highest PPV (0.54), minimal uncertainty interval (11.6%), and the highest proportion of correctly classified patients (76%); followed by LSM (PPV: 0.43, uncertainty interval: 15.5%, correct classification rate: 66%), and FIB-4 (PPV: 0.42, uncertainty interval: 26.1%, correct classification rate: 62.6%) in terms of identifying advanced-stage liver fibrosis. Combined model analysis demonstrated that FIB-4 combined with Agile 3+ had improved the correct classification rate and reduced the proportion of missed patients compared with FIB-4 combined with LSM. Conclusion:The Agile 3+ score is superior than LSM, FIB-4, NFS, and APRI index at identifying advanced-stage fibrosis in patients with CHB combined with MAFLD. This study supports the use of FIB-4 index combined with Agile 3+ for risk stratification in patients with CHB combined with MAFLD.