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. © Author(s) 2019.