title: A model to predict long-term sustained response to interferon therapy in chronic hepatitis C.
abstract: Interferon therapy is used widely for chronic hepatitis C but only a minority of treated patients achieve a long-lasting sustained response. We have developed, by logistic regression, a mathematical model to estimate the probability of sustained response in an individual patient with chronic hepatitis C when treated with interferon-alpha (IFN-alpha). The model, which includes age, sex, disease duration, pretreatment serum gamma-glutamyl-transpeptidase, alanine aminotransferase and virus genotype, was developed from a database of 307 patients and validated in a new set of 200 patients. It performed well as goodness-of-fit (P = 0.71 and P = 0.15 in the development and test sample, respectively) and discrimination (area under receiver operating curve = 0.79 in the development and 0.78 in the test sample, respectively). This model may provide decision support in the treatment of chronic hepatitis C with IFN-alpha.
authors.affiliation: Department of Clinical and Experimental Medicine, University of Padova, Italy.
authors.forename: F
authors.initials: F
authors.lastname: Noventa
authors.forename: G L
authors.initials: GL
authors.lastname: De Salvo
authors.forename: L
authors.initials: L
authors.lastname: Chemello
authors.forename: P
authors.initials: P
authors.lastname: Pontisso
authors.forename: A
authors.initials: A
authors.lastname: Alberti
mesh_terms: D000328:Adult; D000998:Antiviral Agents / Q000627:therapeutic use*; D002908:Chronic Disease; D005260:Female; D006526:Hepatitis C / Q000188:drug therapy*; D006801:Humans; D016898:Interferon-alpha / Q000627:therapeutic use*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008954:Models, Biological; D011336:Probability; D013997:Time Factors
chemical_list: D000998:Antiviral Agents; D016898:Interferon-alpha