Univariate and multivariate logistic analyses were performed to i

Univariate and multivariate logistic analyses were performed to identify selleck chemicals variables that were independently correlated with the treatment outcome. Variables with a P value of <0.1 in univariate analysis were further included in a multivariate logistic regression

analysis. The odds ratios and 95% CI were also calculated. All statistical analyses were performed using SPSS version 16 software (SPSS, Chicago, IL, USA). Unless otherwise stated, a P value of <0.05 was considered statistically significant. The sequence data reported in this paper have been deposited in the DDBJ/EMBL/GenBank nucleotide sequence databases under the accession numbers AB601987 through AB602043. Among the 57 patients enrolled in this study, 8 (14%), 36 (63%), 42 (74%) and 32 (56%) patients were negative for HCV-RNA at week 4 (RVR), week 12 (EVR), week 48 (ETR) and week 72 (SVR), respectively (Table 1). SVR was achieved by all (100%) of RVR, 30 (83%) of 36 EVR, and 32 (76%) of 42 ETR patients. Non-SVR patients represented 44% (25/57) of total cases. Twenty-six percent (15/57) of the patients had continuous viremia during the whole observation period (72 weeks), referred to as a null response; whereas 18% (10/57) had transient disappearance of serum HCV RNA at a certain time point followed by a rebound in viremia

either before, or after the end of, the treatment course, referred to as a relapse. The degree of sequence variation within the IRRDR has been proposed as a useful predictor of HCV treatment outcome (11, 15, 20, 21). We performed ROC curve analysis to estimate the optimal cutoff number of IRRDR mutations that learn more differentiated between a SVR and non-SVR in the present patient cohort. Based on the results obtained, we estimated

four mutations as the optimal number of IRRDR mutations since this provided the highest sensitivity (88%) and good specificity (52%) with an AUC of 0.66 (Fig. 1a). In this study, check therefore, we used the criteria of four or more mutations in the IRRDR (IRRDR ≥ 4) and IRRDR ≤ 3. In this connection, it should be stated that the criteria of IRRDR ≥ 6 and IRRDR ≤ 5 which were used on different patient cohorts in Hyogo Prefecture (11, 15) were not selected by the ROC curve analysis in this study because of their low sensitivity (34%), although they had higher specificity (80%) than that of IRRDR ≥ 4 (52%). This difference was probably due to the low prevalence of HCV isolates with IRRDR ≥ 6 (28%) in the present patient cohort. We found that 70%, 30%, 17.5% and 12.5% of patients infected with HCV isolates with IRRDR ≥ 4 were SVR, non-SVR, null response and relapse cases, respectively (Table 2 and Fig. 2). By contrast, 24%, 76%, 47% and 29% of patients infected with HCV isolates with IRRDR ≤ 3 were SVR, non-SVR, null response and relapse cases, respectively. Thus, the proportions of SVR, non-SVR, null response and relapse cases were significantly different among HCV isolates with IRRDR ≥ 4 and IRRDR ≤ 3.

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