Interferon-α for chronic hepatitis C: An analysis of pretreatment clinical predictors of response

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Abstract
To identify predictors of short-term and sustained ALT normalization after interferon treatment in adult patients with chronic hepatitis C, we performed a metanalysis of individual patients’ data, with construction and cross-validation of a prediction rule, in 361 patients from two randomized trials. In one trial, 116 subjects with transfusion-related chronic hepatitis C were treated with lymphoblastoid interferon (5 MU/m2 three times a week for 2 mo, then 3 MU/m2 three times a week for 4 or 10 mo). In the other study, 245 patients with community-acquired chronic hepatitis C received recombinant interferon-α2b (10 MU three times a week for 2 mo, then 5 MU three times a week for 4 mo; then random allocation of subjects with normal aminotransferase levels to stop or continue interferon for a further 6 mo). Overall, 164 subjects (45%; 95% confidence interval, 40% to 50%) had short-term responses; 61 (18%; 95% confidence interval, 14% to 22%) maintained sustained responses. Sixty patients (17%; 95% confidence interval, 13% to 21%) withdrew from treatment because of side effects or subjective intolerance. Logistic regression analysis showed that short-term and sustained response were independently predicted by lobular structure on pretreatment liver biopsy (p < 0.0001) and by short disease duration, defined as the time elapsed since transfusion in posttransfusion cases or since the first observation of abnormal aminotransferase levels in cryptogenic disease (p < 0.01). Rules to predict short-term and sustained response to interferon were derived from these items, showing a discriminatory ability of 0.73 and 0.70. We conclude that, in patients with C hepatitis, presence of cirrhosis and long disease duration predict low likelihood of response to interferon. Although the predictive rule based on these items is not sufficiently accurate for decision-making in individual patients, it can definitely assist when applied to groups of patients for planning or interpreting therapeutic studies. The addition of virological features such as quantitation of viremia and hepatitis C virus genotypes may improve the ability to predict treatment outcomes. (Hepatology 1994;19:820-828.)