A predictive model of treatment outcome in patients with chronic HCV infection using IL28B and PD-1 genotyping

Background & Aims The advent of new chronic hepatitis C virus (HCV) therapies requires characterization of patients in order to predict adequate treatment. A good candidate marker is Programmed Cell Death-1 (PD-1) which is involved in progression of HCV infection. The aim of this study was to analyse the effect of several single nucleotide polymorphisms of PD-1 gene and several previously associated factors (IL28B and KIR receptors) on treatment responses. Methods 407 HCV chronic infected patients treated with PEG-IFN-α and ribavirin were recruited and classified according to their response to treatment. They were genotyped for PD-1 and IL28B polymorphisms, killer immunoglobulin-like receptors ( KIR ) and HLA genes. A multivariate logistic regression analysis and a Chi-squared Automatic Interaction Detector (CHAID) prediction model of response included these and other clinical parameters. Results Our results showed that PD-1.3 /A allele was significantly associated with sustained virological response (SVR) in a multivariate logistic regression analysis ( p