title: Predicting diabetes: clinical, biological, and genetic approaches: data from the Epidemiological Study on the Insulin Resistance Syndrome (DESIR).
abstract: OBJECTIVE
  To provide a simple clinical diabetes risk score and to identify characteristics that predict later diabetes using variables available in the clinic setting as well as biological variables and polymorphisms.
  
  
  METHODS
  Incident diabetes was studied in 1,863 men and 1,954 women, 30-65 years of age at baseline, with diabetes defined by treatment or by fasting plasma glucose >or=7.0 mmol/l at 3-yearly examinations over 9 years. Sex-specific logistic regression equations were used to select variables for prediction.
  
  
  RESULTS
  A total of 140 men and 63 women developed diabetes. The predictive clinical variables were waist circumference and hypertension in both sexes, smoking in men, and diabetes in the family in women. Discrimination, as measured by the area under the receiver operating curves (AROCs), were 0.713 for men and 0.827 for women, a little higher than for the Finish Diabetes Risk (FINDRISC) score, with fewer variables in the score. Combining clinical and biological variables, the predictive equation included fasting glucose, waist circumference, smoking, and gamma-glutamyltransferase for men and fasting glucose, BMI, triglycerides, and diabetes in family for women. The number of TCF7L2 and IL6 deleterious alleles was predictive in both sexes, but after including the above clinical and biological variables, this variable was only predictive in women (P < 0.03) and the AROC statistics increased only marginally.
  
  
  CONCLUSIONS
  The best clinical predictor of diabetes is adiposity, and baseline glucose is the best biological predictor. Clinical and biological predictors differed marginally between men and women. The genetic polymorphisms added little to the prediction of diabetes.
authors.affiliation: INSERM U780-IFR69, Villejuif, France/University Paris-Sud, Orsay, France. beverley.balkau@inserm.fr
authors.forename: Beverley
authors.initials: B
authors.lastname: Balkau
authors.forename: Céline
authors.initials: C
authors.lastname: Lange
authors.forename: Leopold
authors.initials: L
authors.lastname: Fezeu
authors.forename: Jean
authors.initials: J
authors.lastname: Tichet
authors.forename: Blandine
authors.initials: B
authors.lastname: de Lauzon-Guillain
authors.forename: Sebastien
authors.initials: S
authors.lastname: Czernichow
authors.forename: Frederic
authors.initials: F
authors.lastname: Fumeron
authors.forename: Philippe
authors.initials: P
authors.lastname: Froguel
authors.forename: Martine
authors.initials: M
authors.lastname: Vaxillaire
authors.forename: Stephane
authors.initials: S
authors.lastname: Cauchi
authors.forename: Pierre
authors.initials: P
authors.lastname: Ducimetière
authors.forename: Eveline
authors.initials: E
authors.lastname: Eschwège
mesh_terms: D000328:Adult; D000368:Aged; D049628:Body Size; D003920:Diabetes Mellitus / Q000453:epidemiology* / Q000235:genetics* / Q000503:physiopathology; D005260:Female; D005602:France / Q000453:epidemiology; D006801:Humans; D006973:Hypertension / Q000453:epidemiology; D015994:Incidence; D007333:Insulin Resistance / Q000235:genetics* / Q000502:physiology; D008297:Male; D008487:Medical History Taking; D008875:Middle Aged; D011237:Predictive Value of Tests; D012907:Smoking / Q000453:epidemiology