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

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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.

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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

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Acknowledgements

We thank all the participants in the Botnia study and MPP.

Funding

The Botnia study was supported by grants from the Sigrid Juselius Foundation, Folkhälsan Research Foundation, Signe and Ane Gyllenberg Foundation, Swedish Cultural Foundation in Finland, Finnish Diabetes Research Foundation, Foundation for Life and Health in Finland, Finnish Medical Society, Paavo Nurmi Foundation, Helsinki University Central Hospital Research Foundation, Perklén Foundation, Ollqvist Foundation, Närpes Health Care Foundation and Ahokas Foundation. The study was also supported by the Municipal Heath Care Center and Hospital in Jakobstad and Health Care Centers in Vasa, Närpes and Korsholm. The skilful assistance of the Botnia Study Group is gratefully acknowledged.

The MPP was supported by grants from the Swedish Research Council (including Linné grant 31475113580), the Heart and Lung Foundation, the Diabetes Research Society, a Nordic Center of Excellence Grant in Disease Genetics, the Diabetes Program at the Lund University, the European Foundation for the Study of Diabetes, the Påhlsson Foundation, the Craaford Foundation, the Novo Nordisk Foundation, the European Network of Genomic and Genetic Epidemiology and the Wallenberg Foundation.

DM is supported by a Canada Research Chair.

Duality of interest

LG has been a consultant for and served on advisory boards for Tethys Bioscience, Sanofi-Aventis, GlaxoSmithKline, Eli Lilly, Merck and Novartis; also he has lectured at meetings organised by Novartis, GlaxoSmithKline and Sanofi-Aventis and received grant support from Novartis. VL received consulting fees from Tethys Bioscience. All other authors declare that there is no duality of interest associated with their contribution to this manuscript.

Contribution statement

All authors have made substantial contributions to the manuscript. AA, DM, PA, JD, VL and LG contributed to the study concept and design. Acquisition of data was carried out by AA, DM, MA, BI, PN, TT, VL and LG. Data analyses and interpretation were performed by AA, DM, PA, MA, TT, VL and LG. The manuscript was drafted by AA and DM. The manuscript was critically reviewed for important intellectual content by PA, MA, JD, BI, PN, TT, VL and LG. All authors have approved the final draft for publication. DM and LG had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Author information

Authors and Affiliations

  1. Department of Clinical Epidemiology and Biostatistics, McMaster University, Michael DeGroote Centre for Learning & Discovery, Room 3205, 1280 Main Street West, Hamilton, ON, L8S 4K1, Canada

    Akram Alyass & David Meyre

  2. Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden

    Peter Almgren, Mikael Akerlund, Valeriya Lyssenko & Leif Groop

  3. Department of Biology, McMaster University, Hamilton, Canada

    Jonathan Dushoff

  4. Folkhälsan Research Center, Helsinki, Finland

    Bo Isomaa

  5. Department of Social Services and Health Care, Jakobstad, Finland

    Bo Isomaa

  6. Department of Clinical Sciences, Scania University Hospital Malmö, Lund University, Malmö, Sweden

    Peter Nilsson

  7. Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland

    Tiinamaija Tuomi

  8. Department of Medicine, Helsinki University Central Hospital and Research Program for Molecular Medicine, Helsinki, Finland

    Tiinamaija Tuomi

Authors
  1. Akram Alyass
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  2. Peter Almgren
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  3. Mikael Akerlund
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  4. Jonathan Dushoff
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  5. Bo Isomaa
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  6. Peter Nilsson
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  7. Tiinamaija Tuomi
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  8. Valeriya Lyssenko
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  9. Leif Groop
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  10. David Meyre
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Corresponding author

Correspondence to David Meyre.

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Alyass, A., Almgren, P., Akerlund, M. et al. Modelling of OGTT curve identifies 1 h plasma glucose level as a strong predictor of incident type 2 diabetes: results from two prospective cohorts. Diabetologia 58, 87–97 (2015). https://doi.org/10.1007/s00125-014-3390-x

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  • DOI: https://doi.org/10.1007/s00125-014-3390-x

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