title: Predicting major outcomes in type 1 diabetes: a model development and validation study.
abstract: OBJECTIVE
  Type 1 diabetes is associated with a higher risk of major vascular complications and death. A reliable method that predicted these outcomes early in the disease process would help in risk classification. We therefore developed such a prognostic model and quantified its performance in independent cohorts.
  
  
  METHODS
  Data were analysed from 1,973 participants with type 1 diabetes followed for 7 years in the EURODIAB Prospective Complications Study. Strong prognostic factors for major outcomes were combined in a Weibull regression model. The performance of the model was tested in three different prospective cohorts: the Pittsburgh Epidemiology of Diabetes Complications study (EDC, n = 554), the Finnish Diabetic Nephropathy study (FinnDiane, n = 2,999) and the Coronary Artery Calcification in Type 1 Diabetes study (CACTI, n = 580). Major outcomes included major CHD, stroke, end-stage renal failure, amputations, blindness and all-cause death.
  
  
  RESULTS
  A total of 95 EURODIAB patients with type 1 diabetes developed major outcomes during follow-up. Prognostic factors were age, HbA1c, WHR, albumin/creatinine ratio and HDL-cholesterol level. The discriminative ability of the model was adequate, with a concordance statistic (C-statistic) of 0.74. Discrimination was similar or even better in the independent cohorts, the C-statistics being: EDC, 0.79; FinnDiane, 0.82; and CACTI, 0.73.
  
  
  CONCLUSIONS
  Our prognostic model, which uses easily accessible clinical features can discriminate between type 1 diabetes patients who have a good or a poor prognosis. Such a prognostic model may be helpful in clinical practice and for risk stratification in clinical trials.
authors.affiliation: Division of Human Nutrition, Wageningen University, Bomenweg 2, PO Box 8129, 6700 EV, Wageningen, the Netherlands, sabita.soedamah-muthu@wur.nl.
authors.forename: Sabita S
authors.initials: SS
authors.lastname: Soedamah-Muthu
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Vergouwe
authors.forename: Tina
authors.initials: T
authors.lastname: Costacou
authors.forename: Rachel G
authors.initials: RG
authors.lastname: Miller
authors.forename: Janice
authors.initials: J
authors.lastname: Zgibor
authors.forename: Nish
authors.initials: N
authors.lastname: Chaturvedi
authors.forename: Janet K
authors.initials: JK
authors.lastname: Snell-Bergeon
authors.forename: David M
authors.initials: DM
authors.lastname: Maahs
authors.forename: Marian
authors.initials: M
authors.lastname: Rewers
authors.forename: Carol
authors.initials: C
authors.lastname: Forsblom
authors.forename: Valma
authors.initials: V
authors.lastname: Harjutsalo
authors.forename: Per-Henrik
authors.initials: PH
authors.lastname: Groop
authors.forename: John H
authors.initials: JH
authors.lastname: Fuller
authors.forename: Karel G M
authors.initials: KG
authors.lastname: Moons
authors.forename: Trevor J
authors.initials: TJ
authors.lastname: Orchard
mesh_terms: D000328:Adult; D003922:Diabetes Mellitus, Type 1 / Q000378:metabolism / Q000503:physiopathology*; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011379:Prognosis; D011446:Prospective Studies
chemical_list: D006442:Glycated Hemoglobin