4 research outputs found
Variants in interferon-alpha pathway genes and response to pegylated interferon-Alpha2a plus ribavirin for treatment of chronic hepatitis C virus infection in the hepatitis C antiviral long-term treatment against cirrhosis trial
Combination treatment with pegylated-interferon-alpha (PEG IFN-Α) and ribavirin, the current recommended therapy for chronic hepatitis C virus (HCV) infection, results in a sustained virological response (SVR) in only about half of patients. Because genes involved in the interferon-alpha pathway may affect antiviral responses, we analyzed the relationship between variants in these genes and SVR among participants in the Hepatitis C Antiviral Long-Term treatment Against Cirrhosis (HALT-C) trial. Patients had advanced chronic hepatitis C that had previously failed to respond to interferon-based treatment. Participants were treated with peginterferon-Α2a and ribavirin during the trial. Subjects with undetectable HCV RNA at week 72 were considered to have had an SVR. Subjects with detectable HCV RNA at week 20 were considered nonresponders. We used TaqMan assays to genotype 56 polymorphisms found in 13 genes in the interferon-alpha pathway. This analysis compares genotypes for participants with an SVR to nonresponders. The primary analysis was restricted to European American participants because a priori statistical power was low among the small number (n = 131) of African American patients. We used logistic regression to control the effect of other variables that are associated with treatment response. Among 581 European American patients, SVR was associated with IFNAR1 IVS1-22G (adjusted odds ratio, 0.57; P = 0.02); IFNAR2 Ex2-33C (adjusted odds ratio, 2.09; P = 0.02); JAK1 IVS22+112T (adjusted odds ratio, 1.66; P = 0.04); and ADAR Ex9+14A (adjusted odds ratio, 1.67; P = 0.03). For the TYK2 -2256A promoter region variant, a borderline association was present among European American participants (OR, 1.51; P = 0.05) and a strong relationship among African American patients; all 10 with SVR who were genotyped for TYK2 -2256 carried the A variant compared with 68 of 120 (57%) nonresponders ( P = 0.006). Conclusion: Genetic polymorphisms in the interferon-Α pathway may affect responses to antiviral therapy of chronic hepatitis C. (H EPATOLOGY 2009.)Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/63061/1/22877_ftp.pd
An IL28B Genotype-Based Clinical Prediction Model for Treatment of Chronic Hepatitis C
BACKGROUND:Genetic variation in IL28B and other factors are associated with sustained virological response (SVR) after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC). Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables. METHODS:HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR) and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC). RESULTS:Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p<.0001); the model also included HCV RNA (log10 IU/ml), AST:ALT ratio, Ishak fibrosis score and prior ribavirin treatment. For this model AUC was 78.5%, compared to 73.0% for a model restricted to the four clinical predictors and 60.0% for a model restricted to IL28B genotype (p<0.001). Subjects with a predicted probability of SVR <10% had an observed SVR rate of 3.8%; subjects with a predicted probability >10% (43.3% of subjects) had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study. CONCLUSION:A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC
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An IL28B Genotype-Based Clinical Prediction Model for Treatment of Chronic Hepatitis C
BackgroundGenetic variation in IL28B and other factors are associated with sustained virological response (SVR) after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC). Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables.MethodsHALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR) and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC).ResultsAmong 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p<.0001); the model also included HCV RNA (log10 IU/ml), AST∶ALT ratio, Ishak fibrosis score and prior ribavirin treatment. For this model AUC was 78.5%, compared to 73.0% for a model restricted to the four clinical predictors and 60.0% for a model restricted to IL28B genotype (p<0.001). Subjects with a predicted probability of SVR <10% had an observed SVR rate of 3.8%; subjects with a predicted probability >10% (43.3% of subjects) had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study.ConclusionA clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC