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Vitamin D levels and IL28B polymorphisms are related to rapid virological response to standard of care in genotype 1 chronic hepatitis C

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ANTIVIRAL THERAPY
卷 17, 期 5, 页码 823-831

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INT MEDICAL PRESS LTD
DOI: 10.3851/IMP2100

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Background: Genotype 1 (G1) chronic hepatitis C (CHC) patients achieving a rapid virological response (RVR) on pegylated interferon (PEG-IFN) plus ribavirin have a high chance of sustained virological response (SVR), influenced by IL28B status, viral load, fibrosis and insulin resistance. We assessed whether 25-hydroxyvitamin D (25[OH] D) serum levels are linked to RVR and can be used together with IL28B to construct a pretreatment model to predict RVR. Methods: A total of 117 consecutive patients with G1 CHC were evaluated by biopsy and anthropometric and metabolic measurements. 25(OH) D serum levels were measured by HPLC. IL28B rs12979860 and rs8099917 polymorphisms were also evaluated. All patients underwent antiviral therapy with PEG-IFN-alpha 2a plus ribavirin. HCV RNA was assessed at baseline, week 4, week 12, at the end of therapy and after 6 months of follow-up. Results: Mean +/- SD 25(OH) D serum levels were 26.3 +/- 10.6 mu g/l (range 8.0-58.0) and 31 (26.5%) patients had the rs12979860 CC polymorphism. RVR was achieved in 35 (29.9%) patients, and 32 (91.4%) of them had an SVR, compared to 26 of 82 (31.7%) without RVR. The rs12979860 CC polymorphism (OR 4.575, 95% CI 1.761, 11.889; P=0.002) and higher 25(OH) D levels (OR 1.055, 95% CI 1.010, 1.101; P=0.01) were independently associated with the achievement of RVR by multivariate analysis. The likelihood of RVR progressively increased from patients in the worst class (vitamin D<26.8 mu g/l and TT/TC polymorphism; RVR 14.2%), to those with only one positive predictor (RVR 29.7% and 37.5%), and to those in the best class (vitamin D >= 26.8 mu g/l and rs12979860 CC polymorphism; RVR 73.3%). Conclusions: In patients with G1 CHC, 25(OH) D serum levels and IL28B status are independently associated with the likelihood to achieve RVR and SVR. When incorporated into a pretreatment predictive model they can assist in further discriminating patients with a high likelihood of achieving RVR and SVR.

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