Early virological response may predict treatment response in sofosbuvir-based combination therapy of chronic hepatitis c in a multi-center “real-life” cohort

BACKGROUND The combination of sofosbuvir (SOF), ribavirin (RBV) and peg-interferon-alfa-2a (peg-IFN-alfa-2a) as well as the combination of SOF and RBV for the treatment of patients infected with hepatitis c virus (HCV) has improved rates of sustained virological response (SVR) considerably in recent trials. However, there is only limited data concerning the efficacy and safety in a "real-life" cohort. METHODS We analyzed a cohort of 119 patients with chronic HCV infection treated at four investigational sites in Germany. All patients received either a combination treatment of SOF, RBV and peg-IFN-alfa-2a or SOF and RBV. RESULTS The rates of SVR at 12 weeks after end of treatment (SVR 12) were as follows: Among 76 patients with genotype 1 infection the SVR 12 rate was 74% (n = 56), among 14 patients with genotype 2 infection the SVR 12 rate was 79% (n = 11), among 24 patients with genotype 3 infection the SVR 12 rate was 92% (n = 22) and among 5 patients with genotype 4 infection the SVR 12 rate was 80% (n = 4). Of all 26 patients with a relapse in our cohort, 69% (n = 18) of these patients presented with liver cirrhosis and 58% (n = 15) were treatment experienced. Notably, the level of HCV-RNA after 4 weeks of treatment was a significant predictor of treatment response in genotype 1 patients. Patients with HCV-RNA levels ≥ 12 IU ml-1 after 4 weeks of treatment achieved SVR 12 only in 30% (n = 17/56, p < 0.0001) of cases and treatment response was even lower with SVR 12 of 25% (n = 5/20, p = 0.0016) in the subgroup of patients with cirrhosis. CONCLUSION We observed a high rate of SVR 12 with SOF-based treatment regimes, however probably due to the high number of patients with liver cirrhosis and prior treatment experience, treatment response rates were lower than in previously published trials. In genotype 1 patients the analysis of early virological response may predict treatment response in SOF-based combination therapies.