4.6 Article

Markers of Collagen Remodeling Detect Clinically Significant Fibrosis in Chronic Hepatitis C Patients

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PLOS ONE
卷 10, 期 9, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0137302

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资金

  1. Danish Science Foundation
  2. Danish Ministry of Science and Technology
  3. NOVO Nordisk Foundation
  4. National and Medical Research Council of Australia [1053206, 632630, 1049857, 1047417]
  5. Robert W. Storr Bequest
  6. Novo Nordisk Fonden [NNF10OC1013267] Funding Source: researchfish

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Background and Aim Detection of advanced fibrosis (Metavir F >= 3) is important to identify patients with a high urgency of antiviral treatments vs. those whose treatment could be deferred (F <= 2). The aim was to assess the diagnostic value of novel serological extracellular matrix protein fragments as potential biomarkers for clinically significant and advanced fibrosis. Methods Specific protein fragments of matrix metalloprotease degraded type I, III, IV and VI collagen (C1M, C3M, C4M, C6M) and type III and IV collagen formation (Pro-C3 and P4NP7S) were assessed in plasma from 403 chronic hepatitis C patients by specific ELISAs. Patients were stratified according to Metavir Fibrosis stage; F0 (n = 46), F1 (n = 161), F2 (n = 95), F3 (n = 44) and F4 (n = 33) based on liver biopsy. Results Pro-C3 was significantly elevated in patients with significant fibrosis (>= F2) compared to F0-F1 (p< 0.05), while the markers C3M, C4M, C6M and P4NP7S were significantly elevated in patients with advanced fibrosis (>= F3) compared to F0-F2 (p< 0.05). C1M showed no difference between fibrosis stages. Using Receiver Operating Characteristics analysis, the best marker for detecting >= F2 and >= F3 was Pro-C3 with AUC = 0.75 and AUC = 0.86. Combination of Pro-C3 and C4M with age, BMI and gender in a multiple ordered logistic regression model improved the diagnostic value for detecting >= F2 and >= F3 with AUC = 0.80 and AUC = 0.88. Conclusion The Pro-C3 protein fragment provided clinically relevant diagnostic accuracy as a single marker of liver fibrosis. A model combining Pro-C3 and C4M along with patient's age, body mass index and gender increased the diagnostic power for identifying clinically significant fibrosis.

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