title: [Comparison of multiple prediction models for hypertension (Neural networks, logistic regression and flexible discriminant analyses)].
abstract: OBJECTIVE
  In this study, we compared performances of logistic regression analysis (LR), flexible discriminant analysis (EAA) and neural networks (SA) in prediction of primary hypertension.
  
  
  METHODS
  Predictor variables were family history, lipoprotein A, triglyceride, smoking and body mass index. The data were collected from Cardiology Clinic of Trakya University Medical Faculty in Turkey, 2001. Logistic regression analysis, flexible discriminant analysis and neural networks were used for prediction of control and hypertension groups. Comparison of the performance of all models was done using receiver operating characteristic (ROC) curve analysis.
  
  
  RESULTS
  All models had areas under the ROC curve in the range of 0.793-0.984 and SA had sensitivity, specificity, and accuracy greater than 90% at ideal threshold. ROC curve areas of SA and LR, and SA and EAA were statistically different (p<0.001 and p<0.001 respectively), while ROC curve areas of EAA and LR did not differ (p>0.05).
  
  
  CONCLUSIONS
  We concluded that family history, lipoprotein A, triglyceride, smoking and body mass index variables can be used for prediction of control and hypertension groups with statistically better performance of SA over LR and EAA.
authors.affiliation: Department of Biostatistics, Medical Faculty, Trakya University, Edirne 22030, Turkey. ture@trakya.edu.tr
authors.forename: Mevlüt
authors.initials: M
authors.lastname: Türe
authors.forename: Imran
authors.initials: I
authors.lastname: Kurt
authors.forename: Ebru
authors.initials: E
authors.lastname: Yavuz
authors.forename: Turhan
authors.initials: T
authors.lastname: Kürüm
mesh_terms: D015992:Body Mass Index; D016022:Case-Control Studies; D016002:Discriminant Analysis; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000175:diagnosis* / Q000209:etiology; D017270:Lipoprotein(a) / Q000097:blood; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012907:Smoking; D014280:Triglycerides / Q000097:blood
chemical_list: D017270:Lipoprotein(a); D014280:Triglycerides