A novel model for detecting advanced fibrosis in patients with nonalcoholic fatty liver disease

Xinyu Yang; Mingfeng Xia; Xinxia Chang; Xiaopeng Zhu; Xiaoyang Sun; Yinqiu Yang; Liu Wang; Qiling Liu; Yuying Zhang; Yanlan Xu; Huandong Lin; Lin Liu; Xiuzhong Yao; Xiqi Hu; Jian Gao; Hongmei Yan; Xin Gao; Hua Bian

doi:10.1002/dmrr.3570

A novel model for detecting advanced fibrosis in patients with nonalcoholic fatty liver disease

Diabetes Metab Res Rev. 2022 Nov;38(8):e3570. doi: 10.1002/dmrr.3570. Epub 2022 Aug 17.

Authors

Xinyu Yang^{1

2}, Mingfeng Xia^{1

2}, Xinxia Chang^{1

2}, Xiaopeng Zhu^{1

2}, Xiaoyang Sun^{1

2}, Yinqiu Yang^{1

2}, Liu Wang^{1

2

3}, Qiling Liu^{1

2}, Yuying Zhang^{1

2}, Yanlan Xu^{1

2

4}, Huandong Lin^{1

2}, Lin Liu^{1

2}, Xiuzhong Yao⁵, Xiqi Hu⁶, Jian Gao⁷, Hongmei Yan^{1

2}, Xin Gao^{1

2}, Hua Bian^{1

2

8}

Affiliations

¹ Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.
² Fudan Institute for Metabolic Disease, Fudan University, Shanghai, China.
³ Second Affiliated Hospital of Army Military Medical University, Chongqing, China.
⁴ Department of Geriatrics, Qingpu Branch of Zhongshan Hospital, Fudan University, Shanghai, China.
⁵ Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.
⁶ Department of Pathology, Shanghai Medical College, Fudan University, Shanghai, China.
⁷ Department of Clinical Nutrition, Zhongshan Hospital, Center of Clinical Epidemiology, EBM of Fudan University, Fudan University, Shanghai, China.
⁸ Department of Endocrinology and Metabolism, Wusong Branch of Zhongshan Hospital, Fudan University, Shanghai, China.

Abstract

Aims: The study aimed to develop a novel noninvasive model to detect advanced fibrosis based on routinely available clinical and laboratory tests.

Materials and methods: A total of 309 patients who underwent liver biopsy were randomly divided into the estimation group (n = 201) and validation group (n = 108). The model was developed using multiple regression analysis in the estimation group and further verified in the validation group. Diagnostic accuracy was evaluated using the receiver operating characteristic (ROC) curve.

Results: The model was named NAFLD Fibrosis Index (NFI): -10.844 + 0.046 × age - 0.01 × platelet count + 0.19 × 2h postprandial plasma glucose (PG) + 0.294 × conjugated bilirubin - 0.015 × ALT + 0.039 × AST + 0.109 × total iron binding capacity -0.033 × parathyroid hormone (PTH). The area under the ROC curve (AUC) of NFI was 0.86 (95% CI: 0.79-0.93, p < 0.001) in the estimation group and 0.80 (95% CI: 0.69-0.91, p < 0.001) in the validation group, higher than NFS, FIB4, APRI, and BARD, and similar to FibroScan (NFI AUC = 0.77, 95% CI: 0.66-0.89, p = 0.001 vs. FibroScan AUC = 0.76, 95% CI: 0.62-0.90, p = 0.002). By applying the low cut-off value (-2.756), advanced fibrosis could be excluded among 49.3% and 48% of patients in the estimation group (sensitivity: 93.1%, NPV: 97.9%, specificity: 55.2%, and PPV: 26.0%) and validation group (sensitivity: 81.3%, NPV: 94.2%, specificity: 53.3%, and PPV: 23.2%), respectively, allowing them to avoid liver biopsy.

Conclusions: The study has established a novel model for advanced fibrosis, the diagnostic accuracy of which is superior to the current clinical scoring systems and is similar to FibroScan.

Keywords: advanced fibrosis; diagnosis; logistic models; nonalcoholic fatty liver disease.

Publication types

Randomized Controlled Trial
Research Support, Non-U.S. Gov't

MeSH terms

Alanine Transaminase
Aspartate Aminotransferases
Biopsy
Humans
Infant, Newborn
Liver / diagnostic imaging
Liver Cirrhosis / pathology
Non-alcoholic Fatty Liver Disease* / complications
Non-alcoholic Fatty Liver Disease* / diagnosis
Predictive Value of Tests
ROC Curve
Severity of Illness Index

Substances

Aspartate Aminotransferases
Alanine Transaminase