4.7 Article

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

Journal

DIABETOLOGIA
Volume 61, Issue 5, Pages 1135-1141

Publisher

SPRINGER
DOI: 10.1007/s00125-018-4568-4

Keywords

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

Funding

  1. Ministry of Science and Research of the State of North Rhine-Westphalia (MIWF NRW)
  2. German Federal Ministry of Health (BMG)
  3. Federal Ministry for Research (BMBF)
  4. Helmholtz Alliance to Universities (ICEMED)
  5. German Research Foundation (DFG) [SFB 1116]
  6. German Diabetes Association (DDG)
  7. Schmutzler-Stiftung
  8. European Foundation for the Study of Diabetes (Novo Nordisk type 2 diabetes grant)
  9. Austrian Science Foundation [P15656]
  10. Austrian National Bank [OENB 11459]
  11. Austrian Diabetes Association
  12. Danish Ministry of Science, Technology and Innovation
  13. Danish Diabetes Association
  14. Novo Nordisk Foundation
  15. Foundation of Gerda and Aage Haensch
  16. EXGENESIS from the European Union [005272]
  17. European Foundation for the Study of Diabetes (EFSD)
  18. Ministry of Health, Czech Republic - conceptual development of research organization (Institute of Endocrinology) [EU 00023761]
  19. Italian Ministry of University and Scientific Research [2001065883-001]
  20. European Foundation for the Study of Diabetes (GSK grant)

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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.

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