title: A risk score for type 1 diabetes derived from autoantibody-positive participants in the diabetes prevention trial-type 1.
abstract: OBJECTIVE
  The accurate prediction of type 1 diabetes is essential for appropriately identifying prevention trial participants. Thus, we have developed a risk score for the prediction of type 1 diabetes.
  
  
  METHODS
  Diabetes Prevention Trial-Type 1 (DPT-1) participants, islet cell autoantibody (ICA)-positive relatives of type 1 diabetic patients (n = 670), were randomly divided into development and validation samples. Risk score values were calculated for the validation sample from development sample model coefficients obtained through forward stepwise proportional hazards regression.
  
  
  RESULTS
  A risk score based on a model including log-BMI, age, log-fasting C-peptide, and postchallenge glucose and C-peptide sums from 2-h oral glucose tolerance tests (OGTTs) was derived from the development sample. The baseline risk score strongly predicted type 1 diabetes in the validation sample (chi(2) = 82.3, P < 0.001). Its strength of prediction was almost the same (chi(2) = 83.3) as a risk score additionally dependent on a decreased first-phase insulin response variable from intravenous glucose tolerance tests (IVGTTs). Biochemical autoantibodies did not contribute significantly to the risk score model. A final type 1 diabetes risk score was then derived from all participants with the same variables as those in the development sample model. The change in the type 1 diabetes risk score from baseline to 1 year was in itself also highly predictive of type 1 diabetes (P < 0.001).
  
  
  CONCLUSIONS
  A risk score based on age, BMI, and OGTT indexes, without dependence on IVGTTs or additional autoantibodies, appears to accurately predict type 1 diabetes in ICA-positive relatives.
authors.affiliation: Division of Endocrinology, University of Miami, P.O. Box 016960 (D110), Miami, FL 33101, USA. jsosenko@med.miami.edu
authors.forename: Jay M
authors.initials: JM
authors.lastname: Sosenko
authors.forename: Jeffrey P
authors.initials: JP
authors.lastname: Krischer
authors.forename: Jerry P
authors.initials: JP
authors.lastname: Palmer
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Mahon
authors.forename: Catherine
authors.initials: C
authors.lastname: Cowie
authors.forename: Carla J
authors.initials: CJ
authors.lastname: Greenbaum
authors.forename: David
authors.initials: D
authors.lastname: Cuthbertson
authors.forename: John M
authors.initials: JM
authors.lastname: Lachin
authors.forename: Jay S
authors.initials: JS
authors.lastname: Skyler
mesh_terms: D000293:Adolescent; D000328:Adult; D001323:Autoantibodies / Q000097:blood*; D001786:Blood Glucose / Q000032:analysis; D002096:C-Peptide / Q000097:blood; D002648:Child; D002675:Child, Preschool; D015331:Cohort Studies; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000175:diagnosis / Q000517:prevention & control*; D005951:Glucose Tolerance Test; D006801:Humans; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D007328:Insulin / Q000627:therapeutic use*; D007515:Islets of Langerhans / Q000276:immunology; D008875:Middle Aged; D011379:Prognosis; D012044:Regression Analysis; D012307:Risk Factors
chemical_list: D001323:Autoantibodies; D001786:Blood Glucose; D002096:C-Peptide; D007004:Hypoglycemic Agents; D007328:Insulin