Diabetologia

, Volume 58, Issue 1, pp 87–97 | Cite as

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

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

Abstract

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 Malmö 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 [AUCROC] 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 (AUCROC 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, AUCROC 0.83 [0.80, 0.86]; MPP, AUCROC 0.74 [0.72, 0.77]). 1h-PG also outperformed HbA1c 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/interpretation

1h-PG is a valuable prediction tool for identifying adults at risk for future type 2 diabetes.

Keywords

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

Abbreviations

1h-PG

1 h post-OGTT plasma glucose

2h-PG

2 h post-OGTT plasma glucose

AUCglucose

AUC for OGTT glucose

AUCROC

AUC for ROC

FPG

Fasting plasma glucose

IFG

Impaired fasting glucose

IGT

Impaired glucose tolerance

MPP

Malmö Prevention Project

NGT

Normal glucose tolerance status

NRI

Net reclassification improvement

PG

Plasma glucose

ROC

Receiver operating characteristic

Supplementary material

125_2014_3390_MOESM1_ESM.pdf (59 kb)
ESM Methods(PDF 59 kb)
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ESM Table 1(PDF 16 kb)
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ESM Table 2(PDF 21 kb)
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ESM Table 3(PDF 22 kb)
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ESM Table 4(PDF 20 kb)
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ESM Table 5(PDF 21 kb)
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ESM Table 9(PDF 20 kb)
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ESM Fig. 1(PDF 20 kb)
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ESM Fig. 2(PDF 75 kb)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Akram Alyass
    • 1
  • Peter Almgren
    • 2
  • Mikael Akerlund
    • 2
  • Jonathan Dushoff
    • 3
  • Bo Isomaa
    • 4
    • 5
  • Peter Nilsson
    • 6
  • Tiinamaija Tuomi
    • 7
    • 8
  • Valeriya Lyssenko
    • 2
  • Leif Groop
    • 2
  • David Meyre
    • 1
  1. 1.Department of Clinical Epidemiology and BiostatisticsMcMaster University, Michael DeGroote Centre for Learning & DiscoveryHamiltonCanada
  2. 2.Department of Clinical Sciences, Diabetes and EndocrinologyLund UniversityMalmöSweden
  3. 3.Department of BiologyMcMaster UniversityHamiltonCanada
  4. 4.Folkhälsan Research CenterHelsinkiFinland
  5. 5.Department of Social Services and Health CareJakobstadFinland
  6. 6.Department of Clinical SciencesScania University Hospital Malmö, Lund UniversityMalmöSweden
  7. 7.Department of General Practice and Primary Health CareUniversity of HelsinkiHelsinkiFinland
  8. 8.Department of MedicineHelsinki University Central Hospital and Research Program for Molecular MedicineHelsinkiFinland

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