title: Comparison of a Bayesian network with a logistic regression model to forecast IgA nephropathy.
abstract: 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.
authors: Département de Néphrologie et Hypertension, Hospices Civils de Lyon, Hôpital Edouard Herriot, 69437 Lyon, France.
authors: Michel
authors: M
authors: Ducher
authors: Emilie
authors: E
authors: Kalbacher
authors: François
authors: F
authors: Combarnous
authors: Jérome
authors: J
authors: Finaz de Vilaine
authors: Brigitte
authors: B
authors: McGregor
authors: Denis
authors: D
authors: Fouque
authors: Jean Pierre
authors: JP
authors: Fauvel
mesh_terms: D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D001706:Biopsy; D005260:Female; D005922:Glomerulonephritis, IGA / Q000097:blood / Q000175:diagnosis* / Q000473:pathology; D006801:Humans; D007070:Immunoglobulin A / Q000097:blood*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D011379:Prognosis; D012372:ROC Curve
chemical_list: D007070:Immunoglobulin A