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World J Gastroenterol. Dec 14, 2005; 11(46): 7318-7322
Published online Dec 14, 2005. doi: 10.3748/wjg.v11.i46.7318
Accuracy of a predictive model for severe hepatic fibrosis or cirrhosis in chronic hepatitis C
Agostino Colli, Alice Colucci, Silvia Paggi, Mirella Fraquelli, Sara Massironi, Marco Andreoletti, Vittorio Michela, Dario Conte
Agostino Colli, Sara Massironi, Marco Andreoletti, Vittorio Michela, Department of Internal Medicine, Ospedale “A. Manzoni”, 23900 Lecco, Italy
Alice Colucci, Silvia Paggi, Mirella Fraquelli, Dario Conte, Postgraduate School of Gastroenterology, IRCCS Ospedale Maggiore, 20122 Milan, Italy
Author contributions: All authors contributed equally to the work.
Supported by the “Research Competition Award 2002” from IRCCS Ospedale Maggiore, Milan, and “Associazione Amici della Gastroenterologia del Granelli”, Milan, Italy
Correspondence to: Dario Conte, MD, Postgraduate School of Gastroenterology, Padiglione Granelli 3° piano, IRCCS -Ospedale Maggiore, Via F. Sforza 35, 20122 Milan, Italy. dario.conte@unimi.it
Telephone: +39-02-55033418 Fax: +39-02-55033644
Received: March 26, 2005
Revised: July 18, 2005
Accepted: July 25, 2005
Published online: December 14, 2005
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: <10% (low), 10-74% (not diagnostic), 75-90% (high) and >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 (<10%) probability of severe fibrosis, 33% with a probability ranging from 75% to 90%, and 33% with an uncertain diagnosis (i.e., a probability ranging from 10% to 74%). The observed frequency of severe fibrosis/cirrhosis was within the predefined ranges.

CONCLUSION: The model can correctly identify 67% of patients with a high (>75%) or low (<10%) probability of cirrhosis, leaving only 33% of the patients still requiring liver biopsy.

Keywords: Liver fibrosis; Ultrasonography; Bonacini score; Liver biopsy; Hepatitis C