Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C

Agostino Colli, Alice Collucci, Silvia Paggi, Mirella Fraquelli, Sara Massironi, Marco Andreoletti, Vittorio Michela, Dario Conte

Research output: Contribution to journalArticle

Abstract

Aim: To assess the accuracy of a model in diagnosing severe fibrosis/cirrhosis in chronic hepatitis C virus (HCV) infection. Methods: The model, based on the sequential combination of the Bonacini score (BS: ALT/AST ratio, platelet count and INR) and ultrasonography liver surface characteristics, was applied to 176 patients with chronic HCV infection. Assuming a pre-test probability of 35%, the model defined four levels of post-test probability of severe fibrosis/cirrhosis: 90% (almost absolute). The predicted probabilities were compared with the observed patients' distribution according to the histology (METAVIR). Results: Severe fibrosis/cirrhosis was found in 67 patients (38%). The model discriminated patients in three comparable groups: 34% with a very high (>90%) or low (75%) or low (

Original languageEnglish
Pages (from-to)7318-7322
Number of pages5
JournalWorld Journal of Gastroenterology
Volume11
Issue number46
Publication statusPublished - Dec 14 2005

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Keywords

  • Bonacini score
  • Hepatitis C
  • Liver biopsy
  • Liver fibrosis
  • Ultrasonography

ASJC Scopus subject areas

  • Gastroenterology

Cite this

Colli, A., Collucci, A., Paggi, S., Fraquelli, M., Massironi, S., Andreoletti, M., Michela, V., & Conte, D. (2005). Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C. World Journal of Gastroenterology, 11(46), 7318-7322.