An artificial neural network improves the non-invasive diagnosis of significant fibrosis in HIV/HCV coinfected patients. Academic Article uri icon

Overview

MeSH

  • Adult
  • Biopsy
  • Cross-Sectional Studies
  • Female
  • Humans
  • Liver
  • Male
  • Neural Networks (Computer)
  • Predictive Value of Tests
  • Retrospective Studies

MeSH Major

  • HIV Infections
  • Hepatitis C, Chronic
  • Liver Cirrhosis

abstract

  • To develop an artificial neural network to predict significant fibrosis (F≥2) (ANN-SF) in HIV/Hepatitis C (HCV) coinfected patients using clinical data derived from peripheral blood. Patients were randomly divided into an estimation group (217 cases) used to generate the ANN and a test group (145 cases) used to confirm its power to predict F≥2. Liver fibrosis was estimated according to the METAVIR score. The values of the area under the receiver operating characteristic curve (AUC-ROC) of the ANN-SF were 0.868 in the estimation set and 0.846 in the test set. In the estimation set, with a cut-off value of <0.35 to predict the absence of F≥2, the sensitivity (Se), specificity (Sp), and positive (PPV) and negative predictive values (NPV) were 94.1%, 41.8%, 66.3% and 85.4% respectively. Furthermore, with a cut-off value of >0.75 to predict the presence of F≥2, the ANN-SF provided Se, Sp, PPV and NPV of 53.8%, 94.9%, 92.8% and 62.8% respectively. In the test set, with a cut-off value of <0.35 to predict the absence of F≥2, the Se, Sp, PPV and NPV were 91.8%, 51.7%, 72.9% and 81.6% respectively. Furthermore, with a cut-off value of >0.75 to predict the presence of F≥2, the ANN-SF provided Se, Sp, PPV and NPV of 43.5%, 96.7%, 94.9% and 54.7% respectively. The ANN-SF accurately predicted significant fibrosis and outperformed other simple non-invasive indices for HIV/HCV coinfected patients. Our data suggest that ANN may be a helpful tool for guiding therapeutic decisions in clinical practice concerning HIV/HCV coinfection. Copyright © 2010 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

publication date

  • January 2011

has subject area

  • Adult
  • Biopsy
  • Cross-Sectional Studies
  • Female
  • HIV Infections
  • Hepatitis C, Chronic
  • Humans
  • Liver
  • Liver Cirrhosis
  • Male
  • Neural Networks (Computer)
  • Predictive Value of Tests
  • Retrospective Studies

Research

keywords

  • Journal Article

Identity

Language

  • eng

Digital Object Identifier (DOI)

  • 10.1016/j.jinf.2010.11.003

PubMed ID

  • 21073895

Additional Document Info

start page

  • 77

end page

  • 86

volume

  • 62

number

  • 1