Table 1.
Patient demographics and clinical characteristics stratified according to Metavir F stages (F0-F4).
Fig 1.
Diagnostic performance of individual Protein Fingerprint markers for detecting HCV patients.
A) Plasma levels of Pro-C3 and P4NP7S, B) Plasma C1M, C3M, C4M and C6M in chronic HCV patients stratified according to Metavir F stages. F0 n = 47, F1 n = 167, F2 n = 107, F3 n = 45 and F4 n = 35. C) Receiver operating characteristic curve (ROC) analysis for the performance of Pro-C3 in distinguishing between F0-F1 (n = 214) and significant fibrosis (≥F2) (n = 186) in chronic HCV patients; D) ROC analysis for the performance of Pro-C3 in distinguishing between F0-F2 (n = 320) and significant fibrosis (≥F3) (n = 80) in chronic HCV patients. Data are shown as geometric mean (95%CI). Asterisks indicate statistical significance indicated by bars. *P<0.05.
Table 2.
Diagnostic performances of Protein Fingerprint markers for the detection of significant (≥F2) and advanced (≥F3) fibrosis.
Fig 2.
Multiple ordered logistic regression models for the detection of fibrosis stratified according to Metavir F stages.
A) Model 1 combining Pro-C3, C4M, AST, and ALT; B) Model 2 combining Pro-C3, C4M, age, BMI, and gender. Data are shown as geometric mean (95%CI) calculated from the algorithms. Asterisks indicate statistical significance indicated by bars. *P<0.05, **P<0.01, ***P<0.001.
Table 3.
Diagnostic performance of combination models for the detection of significant (≥F2) and advanced (≥F3) fibrosis.