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Diabetologia

, Volume 61, Issue 5, pp 1135–1141 | Cite as

Prediction of clamp-derived insulin sensitivity from the oral glucose insulin sensitivity index

  • Andrea Tura
  • Gaetano Chemello
  • Julia Szendroedi
  • Christian Göbl
  • Kristine Færch
  • Jana Vrbíková
  • Giovanni Pacini
  • Ele Ferrannini
  • Michael Roden
Article

Abstract

Aims/hypothesis

The euglycaemic–hyperinsulinaemic clamp is the gold-standard method for measuring insulin sensitivity, but is less suitable for large clinical trials. Thus, several indices have been developed for evaluating insulin sensitivity from the oral glucose tolerance test (OGTT). However, most of them yield values different from those obtained by the clamp method. The aim of this study was to develop a new index to predict clamp-derived insulin sensitivity (M value) from the OGTT-derived oral glucose insulin sensitivity index (OGIS).

Methods

We analysed datasets of people that underwent both a clamp and an OGTT or meal test, thereby allowing calculation of both the M value and OGIS. The population was divided into a training and a validation cohort (n = 359 and n = 154, respectively). After a stepwise selection approach, the best model for M value prediction was applied to the validation cohort. This cohort was also divided into subgroups according to glucose tolerance, obesity category and age.

Results

The new index, called PREDIcted M (PREDIM), was based on OGIS, BMI, 2 h glucose during OGTT and fasting insulin. Bland–Altman analysis revealed a good relationship between the M value and PREDIM in the validation dataset (only 9 of 154 observations outside limits of agreement). Also, no significant differences were found between the M value and PREDIM (equivalence test: p < 0.0063). Subgroup stratification showed that measured M value and PREDIM have a similar ability to detect intergroup differences (p < 0.02, both M value and PREDIM).

Conclusions/interpretation

The new index PREDIM provides excellent prediction of M values from OGTT or meal data, thereby allowing comparison of insulin sensitivity between studies using different tests.

Keywords

Glucose clamp Glucose tolerance Insulin resistance Oral glucose tolerance test Prediction model Validation 

Abbreviations

AIC

Akaike’s information criterion

GIR

Glucose infusion rates

IFG

Impaired fasting glucose

IGT

Impaired glucose tolerance

LOOCV

Leave-one-out cross-validation

NGT

Normal glucose tolerance

MMT

Mixed-meal test

OGIS

Oral glucose insulin sensitivity index

PREDIM

PREDIcted M

Notes

Acknowledgements

The authors wish to thank G. Kacerovsky-Bielesz and A. Brehm (Hanusch-Krankenhaus, Vienna, Austria) and A. Schmid, M. Chmelik and M. Fritsch (Medical University of Vienna, Vienna, Austria) for their help in clarifying some aspects of the data.

Contribution statement

AT analysed the data, developed the model, and wrote the manuscript; GC and CG contributed to the analyses of the data and model development, and drafted the manuscript; JS, KF, JV, EF collected or contributed to collect the data, contributed to the interpretation of the results, and drafted the manuscript; GP contributed to the design of the study, to data analyses and results interpretation, and revised the manuscript critically; MR designed the study, contributed to data analyses and results interpretation, and revised the manuscript critically. All authors approved the final version. MR is the guarantor of this work.

Funding

This study was supported in part by the Ministry of Science and Research of the State of North Rhine-Westphalia (MIWF NRW) and the German Federal Ministry of Health (BMG) to the German Diabetes Center (DDZ), by a grant from the Federal Ministry for Research (BMBF) to the German Center for Diabetes Research (DZD e.V.) as well as by grants from the Helmholtz Alliance to Universities (ICEMED), the German Research Foundation (DFG, SFB 1116), German Diabetes Association (DDG) and the Schmutzler-Stiftung. Data on participants recruited in Vienna were analysed in studies supported by the European Foundation for the Study of Diabetes (Novo Nordisk type 2 diabetes grant, GSK grant), the Austrian Science Foundation (P15656), and the Austrian National Bank (OENB 11459) to MR, and by a Research Grant Award by the Austrian Diabetes Association to Gertrud Kacerovsky-Bielesz, Hanusch-Krankenhaus, Vienna, Austria. The Copenhagen study was supported by the Danish Ministry of Science, Technology and Innovation, the Danish Diabetes Association, the Novo Nordisk Foundation, the Foundation of Gerda and Aage Haensch, and by an EXGENESIS grant (005272) from the European Union. The Prague studies were supported by the grant of the European Foundation for the Study of Diabetes (EFSD) and by the Ministry of Health, Czech Republic - conceptual development of research organization (Institute of Endocrinology – EU 00023761). The San Antonio Metabolism Study was supported by funds from the Italian Ministry of University and Scientific Research (2001065883-001).

Duality of interest

The authors declare that there is no duality of interest associated with this manuscript.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Andrea Tura
    • 1
  • Gaetano Chemello
    • 1
  • Julia Szendroedi
    • 2
    • 3
    • 4
  • Christian Göbl
    • 5
  • Kristine Færch
    • 6
  • Jana Vrbíková
    • 7
  • Giovanni Pacini
    • 1
  • Ele Ferrannini
    • 8
  • Michael Roden
    • 2
    • 3
    • 4
  1. 1.Metabolic UnitCNR Institute of NeurosciencePadovaItaly
  2. 2.Division of Endocrinology and Diabetology, Medical FacultyHeinrich-Heine UniversityDüsseldorfGermany
  3. 3.Institute for Clinical Diabetology, German Diabetes Center (DDZ), Leibniz Center for Diabetes ResearchDüsseldorfGermany
  4. 4.German Center for Diabetes Research (DZD)München-NeuherbergGermany
  5. 5.Department of Obstetrics and Gynecology, Division of Obstetrics and Feto-maternal MedicineMedical University of ViennaViennaAustria
  6. 6.Steno Diabetes Center CopenhagenGentofteDenmark
  7. 7.Institute of EndocrinologyPragueCzech Republic
  8. 8.CNR Institute of Clinical PhysiologyPisaItaly

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