Using conventional statistical analysis and multiple regression analysis, we investigated the viral and host factors that influence the response to recombinant interferon-_2a therapy in patients with chronic hepatitis C. A total of 36 patients was randomly assigned to three administration schedules, 12 patients in each. Response to treatment was set as the criterion variable. Four variables were statistically significant in the conventional method in predicting a good therapeutic outcome: HCV genotype III and IV, lower histology activity index (HAI) score for liver, higher total dose of interferon administration, and lower serum HCV RNA concentration. In multiple regression analysis, a combination of the above four variables resulted in a higher multiple correlation coefficient (R=0.84,P<0.0001) using="" a="" stepwise="" method.="" of="" those="" four,="" hcv="" genotype="" had="" the="" highest="" absolute="" value="" of="" standard="" partial="" regression="" coefficient="" (0.51).="" the="" hcv="" rna="" concentration="" was="" correlated="" with="" hcv="" genotype="" and="" hai="" score,="" whereas="" hcv="" genotype="" and="" hai="" score="" showed="" no="" correlation.="" thus,="" hcv="" rna="" concentration="" was="" not="" statistically="" significant="" in="" multiple="" regression="" analysis.="" these="" findings="" indicate="" that="" hcv="" genotype,="" hai="" score,="" and="" schedule="" of="" administration="" can="" be="" important="" predictors="" of="" the="" response="" to="" interferon="">