title: Use of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for improving the accuracy of the risk classification of type 1 diabetes.
abstract: OBJECTIVE We studied the utility of the Diabetes Prevention Trial-Type 1 Risk Score (DPTRS) for improving the accuracy of type 1 diabetes (T1D) risk classification in TrialNet Natural History Study (TNNHS) participants. RESEARCH DESIGN AND METHODS The cumulative incidence of T1D was compared between normoglycemic individuals with DPTRS values >7.00 and dysglycemic individuals in the TNNHS (n = 991). It was also compared between individuals with DPTRS values <7.00 or >7.00 among those with dysglycemia and those with multiple autoantibodies in the TNNHS. DPTRS values >7.00 were compared with dysglycemia for characterizing risk in Diabetes Prevention Trial-Type 1 (DPT-1) (n = 670) and TNNHS participants. The reliability of DPTRS values >7.00 was compared with dysglycemia in the TNNHS. RESULTS The cumulative incidence of T1D for normoglycemic TNNHS participants with DPTRS values >7.00 was comparable to those with dysglycemia. Among those with dysglycemia, the cumulative incidence was much higher (P < 0.001) for those with DPTRS values >7.00 than for those with values <7.00 (3-year risks: 0.16 for <7.00 and 0.46 for >7.00). Dysglycemic individuals in DPT-1 were at much higher risk for T1D than those with dysglycemia in the TNNHS (P < 0.001); there was no significant difference in risk between the studies among those with DPTRS values >7.00. The proportion in the TNNHS reverting from dysglycemia to normoglycemia at the next visit was higher than the proportion reverting from DPTRS values >7.00 to values <7.00 (36 vs. 23%). CONCLUSIONS DPTRS thresholds can improve T1D risk classification accuracy by identifying high-risk normoglycemic and low-risk dysglycemic individuals. The 7.00 DPTRS threshold characterizes risk more consistently between populations and has greater reliability than dysglycemia.
authors.affiliation: Corresponding author: Jay M. Sosenko, jsosenko@med.miami.edu.
authors.forename: Jay M
authors.initials: JM
authors.lastname: Sosenko
authors.forename: Jay S
authors.initials: JS
authors.lastname: Skyler
authors.forename: Jeffrey
authors.initials: J
authors.lastname: Mahon
authors.forename: Jeffrey P
authors.initials: JP
authors.lastname: Krischer
authors.forename: Carla J
authors.initials: CJ
authors.lastname: Greenbaum
authors.forename: Lisa E
authors.initials: LE
authors.lastname: Rafkin
authors.forename: Craig A
authors.initials: CA
authors.lastname: Beam
authors.forename: David C
authors.initials: DC
authors.lastname: Boulware
authors.forename: Della
authors.initials: D
authors.lastname: Matheson
authors.forename: David
authors.initials: D
authors.lastname: Cuthbertson
authors.forename: Kevan C
authors.initials: KC
authors.lastname: Herold
authors.forename: George
authors.initials: G
authors.lastname: Eisenbarth
authors.forename: Jerry P
authors.initials: JP
authors.lastname: Palmer
mesh_terms: D000328:Adult; D001323:Autoantibodies / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D003922:Diabetes Mellitus, Type 1 / Q000145:classification / Q000453:epidemiology* / Q000517:prevention & control*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015203:Reproducibility of Results; D012307:Risk Factors
chemical_list: D001323:Autoantibodies; D001786:Blood Glucose