Correlation between IP-10 detected in plasma and dried plasma spots.

<p>Samples from 19 patients with chronic hepatitis C infection and no/mild liver fibrosis and 21 patients with liver cirrhosis were compared. There was a highly significant correlation between IP-10 detected with the two methods (r² = 0.97, p<0.0001).</p

A comparison of Receiver Operation Characteristic Curves of IP-10 determined in dried plasma spots and plasma.

<p>Analysis included samples from 21 patients with cirrhosis (regarded as cases) and 19 patients with no/mild fibrosis (regarded controls in the analysis). The Area Under the Curve reflects the markers’ ability to differentiate between the two groups of patients. There was no significant difference between the two methods.</p

IP-10 measurements.

<p>IP-10 measured in plasma (left) and dried plasma spots (right) from 19 patients with chronic hepatitis C infection and no/mild liver fibrosis and 21 patients with liver cirrhosis. Line denote median. There was a significant difference between the groups in both plasma and dried plasma spots, p<0.0004.</p

Hcv_data

Hcv_dat

Predictors of liver cirrhosis (liver stiffness >17.1 kPa).

<p>Predictors of liver cirrhosis (liver stiffness >17.1 kPa).</p

Association between HCV genotype, <i>IL28B</i> genotype and results of transient elastography for 369 patients with chronic hepatitis C virus infection.

<p>Association between HCV genotype, <i>IL28B</i> genotype and results of transient elastography for 369 patients with chronic hepatitis C virus infection.</p

Patient characteristics for 369 patients with chronic hepatitis C virus infection by HCV genotype.

<p>Patient characteristics for 369 patients with chronic hepatitis C virus infection by HCV genotype.</p

pMFAP4 in the patient populations.

<p>SD = standard deviation. Mean and 95% confidence intervals are calculated using transformed values for pMFAP4 and relevant back-transformation, theta = -0.2.</p><p>pMFAP4 in the patient populations.</p

Significantly associated variables in the mixed patient cohort and the DU cohort.

<p>A. Correlation between pMFAP4 and TE in the mixed patient cohort using transformed data. B. Correlation within the DU cohort. Optimal transformations were determined using box-cox analysis. Univariate correlation was investigated by Kendall’s rank test and was significant for both populations (both: p<0.005). C. Variation of TE with pMFAP4 is calculated using median levels of age, HA, platelets, and ALP in the model. D. Variation of TE with HA is calculated using median levels of age, pMFAP4, platelets, and ALP in the model. E. Variation of TE with platelet count is calculated using median levels of age, pMFAP4, HA, and ALP in the model. F. Variation of TE with ALP is calculated using median levels of age, pMFAP4, HA, platelets, and ALP in the model.</p

pMFAP4 level in the mixed patient cohort stratified by Charlson comorbidity group.

<p>The plot shows differences in mean pMFAP4 level between diseased and not-diseased patients according to Charlson comorbidity groups (not-diseased level calculated merging pMFAP4 measurements for all patients without the diagnosis in question). The black horizontal line represents the mean pMFAP4 for the whole population. Light gray circles illustrate the mean pMFAP4 value in the diagnosis group; the black circles illustrate the mean pMFAP4 of the remaining patients without diagnosis. The number of patients with the diagnosis in question is indicated. * Mean pMFAP4 significantly different from the rest of the cohort by the Wilcoxon rank sum test.</p