title: Factors predictive of a beneficial response to therapy of hepatitis C.
abstract: Alpha interferon is the only drug that has been shown to be effective in the treatment of chronic hepatitis C, but only half of patients respond, either transiently or permanently. Pretreatment features that are associated with a greater likelihood of response to short courses of interferon include low hepatitis C virus (HCV) RNA levels, viral genotypes 2 or 3, and the absence of fibrosis or cirrhosis on liver biopsy. Each of these features is more predictive of sustained response (SR) than the end-of-treatment response (ETR). However, the accuracy of these features in predicting response in individual patients is poor. Furthermore, there are several limitations to using these factors in the clinical management of patients. Most importantly, they were identified in 6-month treatment trials. Longer treatment or combination of interferon with ribavirin reduces relapses and will therefore lessen the association of these factors with long-term response. In addition, changes in the definition of treatment end points and the technology used to measure HCV RNA might change the association between these predictive factors and response. The best predictor of a treatment response is the early normalization of the serum alanine aminotransferase (ALT) level during interferon treatment. HCV RNA loss during treatment may also be helpful in predicting response, but it is probably no better than serum ALT levels and is expensive. In summary, several clinical and virological features are associated with higher response rates to interferon treatment. Although pretreatment factors do not accurately predict treatment outcome in individuals, they may be helpful in counseling patients and making treatment decisions.
authors.affiliation: Section of Hepatobiliary Diseases, University of Florida College of Medicine, Gainesville 32610-0214, USA.
authors.forename: G L
authors.initials: GL
authors.lastname: Davis
authors.forename: J Y
authors.initials: JY
authors.lastname: Lau
mesh_terms: D000465:Algorithms; D005544:Forecasting; D005838:Genotype; D016174:Hepacivirus / Q000235:genetics; D006526:Hepatitis C / Q000150:complications / Q000628:therapy* / Q000821:virology; D006801:Humans; D008103:Liver Cirrhosis / Q000150:complications; D011237:Predictive Value of Tests; D012367:RNA, Viral / Q000032:analysis
chemical_list: D012367:RNA, Viral