Individualized Risk Prediction Of Significant Fibrosis In Non-Alcoholic Fatty Liver Disease Using A Novel Nomogram

Background Fibrosis is deemed to be a pivotal determinant of the long-term prognosis in non-alcoholic fatty liver disease (NAFLD). Objective We aimed to develop a novel nomogram-based non-invasive model to accurately predict significant fibrosis in patients with NAFLD. Methods We designed a prospective cohort study including 207 patients with biopsy-proven NAFLD. Detailed anthropometric and fibrosis-related laboratory parameters were collected. A nomogram was established based on variables that were independently associated with significant fibrosis identified by the logistic regression model. Then it was compared with aspartate aminotransferase-to-platelet ratio index (APRI), NAFLD fibrosis score (NFS), FIB-4 and BARD score. Diagnostic accuracy was assessed according to area under the receiver operator characteristic curve (AUROC), sensitivity, specificity, positive and negative predictive values, and decision curve analysis. Results Variables included in the nomogram were: waist-to-height ratio, hyaluronic acid, procollagen-III-peptide, chitinase-3-like protein 1, and cytokeratine-18 neoepitope M65. The discrimination ability of the nomogram (AUROC = 0.829, 95%CI 0.755-0.904) was significantly superior to APRI (AUROC = 0.670, 95%CI 0.563-0.777), NFS (AUROC = 0.601, 95%CI 0.480-0.722), FIB-4 (AUROC = 0.624, 95%CI 0.511-0.736) and BARD (AUROC = 0.579, 95%CI 0.459-0.699) for significant fibrosis (all p < 0.05). The nomogram showed a larger net benefit to aid in decision-making as to whether biopsy is required. Conclusions This novel nomogram was more accurate, and achieved higher net benefit than APRI, NFS, FIB-4 and BARD to detect significant fibrosis. It can be useful as a non-invasive method to screen >= F2 fibrosis in the overall population with NAFLD.