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Leif Groop

Leif Groop

Principal investigator

Leif Groop

Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts

Author

  • Akram Alyass
  • Peter Almgren
  • Mikael Åkerlund
  • Jonathan Dushoff
  • Bo Isomaa
  • Peter Nilsson
  • Tiinamaija Tuomi
  • Valeriya Lyssenko
  • Leif Groop
  • David Meyre

Summary, in English

Aims/hypothesis The relevance of the OGTT in predicting type 2 diabetes is unclear. We assessed the performance of 14 OGTT glucose traits in type 2 diabetes prediction. Methods We studied 2,603 and 2,386 Europeans from the Botnia study and Malmo Prevention Project (MPP) cohorts with baseline OGTT data. Over a follow-up period of 4.94 years and 23.5 years, 155 (5.95%) and 467 (19.57%) participants, respectively, developed type 2 diabetes. The main outcome was incident type 2 diabetes. Results One-hour plasma glucose (1h-PG) was a fair/good predictor of incident type 2 diabetes in the Botnia study and MPP (AUC for receiver operating characteristic [AUC(ROC)] 0.80 [0.77, 0.84] and 0.70 [0.68, 0.73]). 1h-PG alone outperformed the prediction model of multiple clinical risk factors (age, sex, BMI, family history of type 2 diabetes) in the Botnia study and MPP (AUC(ROC) 0.75 [0.72, 0.79] and 0.67 [0.64, 0.70]). The same clinical risk factors added to 1h-PG modestly increased prediction for incident type 2 diabetes (Botnia, AUC(ROC) 0.83 [0.80, 0.86]; MPP, AUC(ROC) 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA(1c) in predicting type 2 diabetes in the Botnia cohort. A 1h-PG value of 8.9 mmol/l and 8.4 mmol/l was the optimal cut-point for initial screening and selection of high-risk individuals in the Botnia study and MPP, respectively, and represented 30% and 37% of all participants in these cohorts. High-risk individuals had a substantially increased risk of incident type 2 diabetes (OR 8.0 [5.5, 11.6] and 3.8 [3.1, 4.7]) and captured 75% and 62% of all incident type 2 diabetes in the Botnia study and MPP. Conclusions/interpretation1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes.

Department/s

  • Genomics, Diabetes and Endocrinology
  • Internal Medicine - Epidemiology
  • EXODIAB: Excellence of Diabetes Research in Sweden
  • EpiHealth: Epidemiology for Health

Publishing year

2015

Language

English

Pages

87-97

Publication/Series

Diabetologia

Volume

58

Issue

1

Document type

Journal article

Publisher

Springer

Topic

  • Endocrinology and Diabetes

Keywords

  • Incident type 2 diabetes
  • Mathematical modelling
  • One-hour post-OGTT
  • plasma glucose
  • Oral glucose tolerance test
  • Prevention

Status

Published

Research group

  • Genomics, Diabetes and Endocrinology
  • Internal Medicine - Epidemiology

ISBN/ISSN/Other

  • ISSN: 1432-0428