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.