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[Application of serum N -glycan profiling diagnostic model in evaluation of liver fibrosis in patients with hepatitis C].
Cao, X; Zhang, Y; Nan, Y M; Tan, Z N; Chen, C Y; Shang, Q H; Liu, X E; Zhuang, H.
Affiliation
  • Cao X; Department of Microbiology and Center of Infectious Diseases, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China.
  • Zhang Y; Department of Traditional and Western Medical Hepatology, Third Hospital of Hebei Medical University, Hebei, Shijiazhuang 050000, China.
  • Nan YM; Department of Traditional and Western Medical Hepatology, Third Hospital of Hebei Medical University, Hebei, Shijiazhuang 050000, China.
  • Tan ZN; Department of Molecular Biomedical Research, Xian si-da Biotechnology Company Limited, Nanjing 210000, China.
  • Chen CY; Department of Molecular Biomedical Research, Xian si-da Biotechnology Company Limited, Nanjing 210000, China.
  • Shang QH; Department of Liver Disease, No. 88 Hospital of Chinese People's Liberation Army, Tai'an 271000, China.
  • Liu XE; Department of Microbiology and Center of Infectious Diseases, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China.
  • Zhuang H; Department of Microbiology and Center of Infectious Diseases, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China.
Zhonghua Gan Zang Bing Za Zhi ; 28(12): 1023-1029, 2020 Dec 20.
Article in Zh | MEDLINE | ID: mdl-34865350
ABSTRACT

Objective:

To study the changes of serum N-glycan abundance in patients with liver fibrosis at different stages of hepatitis C, and to establish and evaluate the diagnostic model for clinical application value.

Methods:

Data of 169 hepatitis C virus-infected cases with liver fibrosis were enrolled. Nine kinds of serum N-glycans were detected and analyzed using DNA sequencer-assisted fluorophore-assisted capillary electrophoresis technology. A binary logistics regression method was used to establish a diagnostic model based on the changes in the relative content of N-glycans in each stage of liver fibrosis. Receiver operating characteristic curve was used to evaluate and compare the diagnostic efficacy with other liver fibrosis diagnostic models.

Results:

N-glycan diagnostic model (B and C) had highest AUROC= 0.776, 0.827 for distinguishing fibrosis S1~S2 to S3~S4 and S1~S3 to S4 than GlycoFibroTest (AUROC = 0.760, 0.807), GlycoCirrhoTest (AUROC = 0.722, 0.787), aspartate aminotransferase to platelet ratio index (AUROC = 0.755, 0.751), FIB-4 index (AUROC = 0.730, 0.774), and S-index (AUROC = 0.707, 0.744). However, the diagnostic efficacy of model A (AUROC = 0.752) for distinguishing fibrosis S1 with S2~S4 had lower diagnostic potency than that of the aspartate aminotransferase to platelet ratio index (AUROC = 0.807). Diagnostic efficiency was improved when the N-glycan profiling and the aspartate aminotransferase to platelet ratio index were combined to diagnose liver fibrosis in each stage, and the area under the receiver operating characteristic curve was 0.839, 0.825, and 0.837, respectively.

Conclusion:

The serum N-glycan profiling diagnostic model has potential clinical application value in the diagnosis of liver fibrosis in patients with hepatitis C.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Hepatitis C / Hepacivirus Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: Zh Journal: Zhonghua Gan Zang Bing Za Zhi Journal subject: GASTROENTEROLOGIA Year: 2020 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Hepatitis C / Hepacivirus Type of study: Diagnostic_studies / Prognostic_studies Limits: Humans Language: Zh Journal: Zhonghua Gan Zang Bing Za Zhi Journal subject: GASTROENTEROLOGIA Year: 2020 Document type: Article Affiliation country: China