A model to predict long-term sustained response to interferon therapy in chronic hepatitis C

F. Noventa, G. L. De Salvo, L. Chemello, P. Pontisso, A. Alberti

Research output: Contribution to journalArticlepeer-review

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-α (IFN-α). The model, which includes age, sex, disease duration, pretreatment serum γ-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-α.

Original languageEnglish
Pages (from-to)193-197
Number of pages5
JournalJournal of Viral Hepatitis
Volume4
Issue number3
Publication statusPublished - May 1997

Keywords

  • Chronic hepatitis C
  • Interferon therapy
  • Logistic regression
  • Predictive model

ASJC Scopus subject areas

  • Hepatology
  • Virology

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