Pretreatment algorithm predicts response to HCV antiviral therapy

Shirakawa H et al. (2008) Pretreatment prediction of virological response to peginterferon plus ribavirin therapy in chronic hepatitis C patients using viral and host factors. Hepatology 48: 1753–1760

Individuals who are chronically infected with HCV genotype 1 and have a high viral load respond poorly to antiviral therapy. Shirakawa and colleagues have now reported a pretreatment algorithm that predicts whether such individuals will successfully respond to treatment.

The study involved 120 patients with chronic HCV genotype 1 infection and high baseline viral loads who were scheduled to receive pegylated interferon α2b and ribavirin treatment. A sustained virological response (SVR) was achieved in 45% of patients and a variety of viral and host factors were analyzed for their ability to predict this response. Logistic regression analysis identified four pretreatment factors that were associated with an SVR: the presence of mutations in the interferon-sensitivity-determining region of HCV, a T_H1:T_H2 ratio ≤15.5, body weight ≥59 kg and neutrophil cell counts ≥2,300 µl. A logistic regression model that incorporated these pretreatment factors categorized patients as having high sensitivity, intermediate sensitivity or low sensitivity to treatment on the basis of their predicted SVR rates. The actual SVR rates were 91% in the high-sensitivity group, 41% in the intermediate-sensitivity group and 15% in the low-sensitivity group. Predicted treatment sensitivities were also associated with the rate of virological response.

This algorithm, therefore, accurately predicts treatment response in groups of patients who are typically difficult to treat, and might avoid the initiation of unnecessary treatment regimens in nonresponsive patients. Validation of this algorithm at other centers is now required.