title: Development and validation of a risk-score model for subjects with impaired glucose tolerance for the assessment of the risk of type 2 diabetes mellitus-The STOP-NIDDM risk-score.
abstract: OBJECTIVE
  To develop a risk-score model, based on available clinical data to assess absolute risk of type 2 diabetes among people with impaired glucose tolerance (IGT).
  
  
  METHODS
  Data from the study to prevent non-insulin dependent diabetes mellitus (STOP-NIDDM) investigating acarbose treatment in individuals with IGT were used to develop multivariable Cox proportional hazards model for the time to onset of diabetes. The final model equation was externally validated using data from the Finnish Cardiovascular Risk Factor (FINRISK) population.
  
  
  RESULTS
  The risk-score model included the variables acarbose treatment, gender, serum triglyceride level, waist circumference, fasting plasma glucose, height, history of cardiovascular disease (CVD) and hypertension. The final model yielded an area under the receiver-operating-characteristic curve (AUC(ROC)) of 0.64 when applied to people with IGT in the STOP-NIDDM, and 0.84 and 0.90 when applied to FINRISK population with IGT alone and IGT and normal glucose tolerance combined, respectively; AUC(ROC) is a measure of the discriminatory power of the model (1, perfect discrimination).
  
  
  CONCLUSIONS
  The STOP-NIDDM risk-score is a simple and validated tool that can identify high-risk individuals with IGT who would benefit most from type 2 diabetes or CVD prevention strategies, such as lifestyle management or early acarbose treatment.
authors.affiliation: Department of Public Health, University of Helsinki, Finland. tuomilehto@hotmail.com
authors.forename: Jaakko
authors.initials: J
authors.lastname: Tuomilehto
authors.forename: Jaana
authors.initials: J
authors.lastname: Lindström
authors.forename: Martin
authors.initials: M
authors.lastname: Hellmich
authors.forename: Walter
authors.initials: W
authors.lastname: Lehmacher
authors.forename: Torsten
authors.initials: T
authors.lastname: Westermeier
authors.forename: Thomas
authors.initials: T
authors.lastname: Evers
authors.forename: Andreas
authors.initials: A
authors.lastname: Brückner
authors.forename: Markku
authors.initials: M
authors.lastname: Peltonen
authors.forename: Qing
authors.initials: Q
authors.lastname: Qiao
authors.forename: Jean-Louis
authors.initials: JL
authors.lastname: Chiasson
mesh_terms: D000328:Adult; D000368:Aged; D015992:Body Mass Index; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology* / Q000517:prevention & control; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology* / Q000517:prevention & control; D003925:Diabetic Angiopathies / Q000145:classification / Q000453:epidemiology; D005260:Female; D018149:Glucose Intolerance / Q000097:blood / Q000150:complications*; D006801:Humans; D006973:Hypertension / Q000150:complications / Q000453:epidemiology; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D014280:Triglycerides / Q000097:blood; D055105:Waist Circumference
chemical_list: D014280:Triglycerides