A statistical analysis of predictive factors of response to human lymphoblastoid interferon in patients with chronic hepatitis C.

Objective: To determine markers predictive of effective interferon treatment for patients with chronic hepatitis C virus (HCV) infection, we studied 80 Japanese patients treated for 6 months with natural interferon-alpha.
Methods: Serum samples were tested for HCV RNA by two-stage polymerase chain reaction (PCR). HCV RNA were grouped into four genotypes by amplification of core-gene sequences by PCR with type-specific primers, and the level of HCV RNA was measured by competitive PCR. HCV RNA was detected in all patients before the interferon treatment. For the purposes of this study, a complete response was defined as the elimination of HCV RNA for at least 6 months after termination of the treatment.
Results: HCV RNA was eliminated from the sera of 27 patients (33.8%) at the termination of the interferon treatment, and the elimination was sustained throughout a 6-month follow-up (complete response). Four of eleven variables proved to be associated with a complete response when assessed by univariate analysis. With multiple logistic regression analysis assessment, however, only two variables (HCV RNA level (p < 0.001) and genotype (p = 0.048)) were significant.
Conclusion: These results suggest that factors associated with the HCV infection are more important than patient characteristics for effective interferon treatment of patients with chronic HCV infection and that a low level of HCV RNA and HCV of genotype III are useful predictors of a complete response.