Development and validation of two models for early prediction of response to therapy in genotype 1 chronic hepatitis C

Early prediction of response to therapy in genotype 1 chronic hepatitis C is difficult. Two predictive models, a pretreatment scoring model (PreT-SM) and a fourth week of therapy scoring model (4w-SM) were constructed in a cohort of 104 patients from a single center (estimation cohort) and validated in a cohort of 141 patients from four independent centers (validation cohort). Individual scores were calculated using variables independently associated with sustained virological response (SVR). Baseline viral load, aspartate aminotransferase/alanine aminotransferase ratio, serum cholesterol, and a numerical score for noninvasive estimation of liver fibrosis were included in the PreT-SM; HCV RNA clearance and PreT-SM scores were included in the 4w-SM. Receiver operating characteristic analysis revealed the area under the curve in the estimation cohort and in the validation cohort to be, respectively, 0.856 and 0.847 for the PreT-SM and 0.908 and 0.907 for the 4w-SM. Low scores were associated with SVR, high scores with non-SVR. The best cutoff scores from the PreT-SM (7 and 9.70) identified, respectively, 36% of patients with SVR and 41% of those with non-SVR from the validation cohort, with high accuracy (> or =90% positive predictive value [PPV] and specificity). Similarly, cutoff scores of 3.20 and 5.60 from the 4w-SM identified, respectively, 71% of patients with SVR and 53% of those with non-SVR from the same cohort with high accuracy (PPV and specificity >92%). In conclusion, these models predicted response to therapy before or after 4 weeks of treatment in approximately 60% of genotype 1 patients and may be valuable for the management of this condition.