Research on the prediction model for progressive fibrosis in patients with NAFLD based on Nomogram

Abstract

Abstract: Objective The degree of fibrosis is considered as a determining factor of long-term prognosis for nonalcoholic fatty liver disease (NAFLD). We aimed to develop a novel non-invasive model based on Nomogram to accurately predict progressive fibrosis in patients with NAFLD. Methods A total of 380 NAFLD patients diagnosed by FibroScan were enrolled. Detailed anthropological data and fibrosis related laboratory parameters were collected. Variables independently associated with advanced fibrosis would be used to construct Nomogram prediction models. Ultimately, the diagnostic efficacy of the prediction model were evaluated by receiver operating characteristic (ROC) curve. Results Variables included in the prediction model were as followed: type 2 diabetes mellitus (OR=1.135, 95%CI 1.019-1.265), aspartate aminotransferase (OR=1.005, 95%CI 1.002-1.018), type III procollagen peptide (OR=1.116, 95%CI 1.028-1.212), and type IV collagen (OR=1.097, 95%CI 1.032-1.166). The area under the ROC curve of the Nomogram prediction model was 0.851, with the 95% CI as 0.778-0.925, the sensitivity as 0.900, and the specificity as 0.826, respectively. Conclusion The novel Nomogram model is more accurate in predicting advanced fibrosis and performs significantly better than the APRI, NFS, FIB-4 and BRAD scores reported in the literature. It might be a noninvasive screening tool for advanced fibrosis in overall NAFLD population.

Key words: Fibrosis, Nonalcoholic fatty liver disease, Nomogram

YANG Yong-qin, WANG Xiao-jun, FENG Gong, LI Rong, LIU Xiao-yu, SUN Xue-mei, HE Na. Research on the prediction model for progressive fibrosis in patients with NAFLD based on Nomogram[J]. Chinese Hepatolgy, 2022, 27(2): 160-163.

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