Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy
Joint Authors
Ducher, Michel
Kalbacher, Emilie
Combarnous, François
Finaz de Vilaine, Jérome
McGregor, Brigitte
Fouque, Denis
Fauvel, Jean Pierre
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-17
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Models are increasingly used in clinical practice to improve the accuracy of diagnosis.
The aim of our work was to compare a Bayesian network to logistic regression to forecast IgA nephropathy (IgAN) from simple clinical and biological criteria.
Retrospectively, we pooled the results of all biopsies (n=155) performed by nephrologists in a specialist clinical facility between 2002 and 2009.
Two groups were constituted at random.
The first subgroup was used to determine the parameters of the models adjusted to data by logistic regression or Bayesian network, and the second was used to compare the performances of the models using receiver operating characteristics (ROC) curves.
IgAN was found (on pathology) in 44 patients.
Areas under the ROC curves provided by both methods were highly significant but not different from each other.
Based on the highest Youden indices, sensitivity reached (100% versus 67%) and specificity (73% versus 95%) using the Bayesian network and logistic regression, respectively.
A Bayesian network is at least as efficient as logistic regression to estimate the probability of a patient suffering IgAN, using simple clinical and biological data obtained during consultation.
American Psychological Association (APA)
Ducher, Michel& Kalbacher, Emilie& Combarnous, François& Finaz de Vilaine, Jérome& McGregor, Brigitte& Fouque, Denis…[et al.]. 2013. Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy. BioMed Research International،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1004862
Modern Language Association (MLA)
Ducher, Michel…[et al.]. Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy. BioMed Research International No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-1004862
American Medical Association (AMA)
Ducher, Michel& Kalbacher, Emilie& Combarnous, François& Finaz de Vilaine, Jérome& McGregor, Brigitte& Fouque, Denis…[et al.]. Comparison of a Bayesian Network with a Logistic Regression Model to Forecast IgA Nephropathy. BioMed Research International. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-1004862
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1004862