Rev Esp Quimioter
September 2007
This study aimed to identify the factors predictive of response before the initiation of treatment and throughout the treatment period in patients with chronic hepatitis C relapse after treatment with interferon-a who were retreated with a standard regimen of interferon-a plus ribavirine and followed up for 40 months. Forty-four patients (40 with genotype 1, four without genotype 1) were included in the study. Four patients (genotype 1) were excluded because of adverse effects.
View Article and Find Full Text PDFThe aims of this study were twofold: i) to evaluate the sustained response rate at 6 months, at 12 months and at the end of the follow-up [(46.39 +/- 9.74 months) (range: 6-60 months)] in patients with chronic hepatitis C retreated with interferon-a (IFN-a) plus ribavirin for 6 months (group A), 12 months (group B), in patients with relapse and those with no response to a previous course of monotherapy with IFN-a; and ii) to evaluate changes in the histological liver lesion.
View Article and Find Full Text PDFObjectives: 1) to identify pretreatment variables predictive of nonresponse to interferon-alpha (IFN-alpha) in patients with chronic hepatitis C, and 2) to establish a prognostic index in these groups using receiver operating characteristics curve analysis.
Methods: 132 patients were treated with IFN-alpha at a dose of 3 megaunits three times a week for 3-12 months. The response was compared in patients with a complete response vs nonresponders, and patients with a sustained response vs nonresponders plus relapsers.
The objectives of this study included: 1) to identify pretreatment variables predictive of absence of response in 107 patients with chronic hepatitis C, genotype 1, treated with interferon-a (IFN-a) at a dose of 3 MU three times weekly for 3-12 months and classified into two groups: group A, nonresponders vs. patients with a complete response, and group B, nonresponding and relapsing patients vs. patients with a sustained response; and 2) to establish a prognostic index using ROC curve analysis.
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