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Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model

  • Endocrine Methods and Techniques
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Abstract

Purpose

Current reference methods for measuring glucose effectiveness (GE) are the somatostatin pancreatic glucose clamp and minimal model analysis of frequently sampled intravenous glucose tolerance test (FSIVGTT), both of which are laborious and not feasible in large epidemiological studies. Consequently, surrogate indices derived from an oral glucose tolerance test (OGTT) to measure GE (oGE) have been proposed and used in many studies. However, the predictive accuracy of these surrogates has not been formally validated. In this study, we used a calibration model analysis to evaluate the accuracy of surrogate indices to predict GE from the reference FSIVGTT (SgMM).

Methods

Subjects (n = 123, mean age 48 ± 11 years; BMI 35.9 ± 7.3 kg/m2) with varying glucose tolerance (NGT, n = 37; IFG/IGT, n = 78; and T2DM, n = 8) underwent FSIVGTT and OGTT on two separate days. Predictive accuracy was assessed by both root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE).

Results

As expected, insulin sensitivity, SgMM, and oGE were reduced in subjects with T2DM and IFG/IGT when compared with NGT. Simple linear regression analyses revealed a modest but significant relationship between oGE and SgMM (r = 0.25, p < 0.001). However, using calibration model, measured SgMM and predicted SgMM derived from oGE were modestly correlated (r = 0.21, p < 0.05) with the best fit line suggesting poor predictive accuracy. There were no significant differences in CVPE and RMSE among the surrogates, suggesting similar predictive ability.

Conclusions

Although OGTT-derived surrogate indices of GE are convenient and feasible, they have limited ability to robustly predict GE.

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Funding

This work was supported by the Intramural Research Programs of NIDDK (R.M.), American Diabetes Association Clinical and Translational Award Number: 0-11-CT-39, and Award Number UL1RR025755 from the National Center for Research Resources, funded by the Office of the Director, National Institutes of Health (NIH) and supported by the NIH Roadmap for Medical Research.

Author contributions

R.M. conceived and designed the study, acquired and analyzed data, drafted and reviewed the manuscript. M.G., S.S., S.G., and B.S.A. analyzed data, drafted, and reviewed the manuscript. R.M. and S.A. performed the statistical analyses and drafted the manuscript T.R.G. and K.O. designed the study, acquired data, and drafted and reviewed the manuscript.

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Authors and Affiliations

  1. Diabetes, Endocrinology, and Obesity Branch, NIDDK, Bethesda, MD, USA

    Michael Glicksman, Shivraj Grewal, Shrayus Sortur, Brent S. Abel, Sungyoung Auh & Ranganath Muniyappa

  2. Nicole Wertheim College of Nursing and Health Sciences, Florida International University, Miami, FL, USA

    Trudy R. Gaillard

  3. Division of Endocrinology, Diabetes and Metabolism, Wexner Medical Center, The Ohio State University, Columbus, OH, USA

    Kwame Osei

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  1. Michael Glicksman
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Correspondence to Ranganath Muniyappa.

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The authors declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Informed consent was obtained from all individual participants in the study.

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Glicksman, M., Grewal, S., Sortur, S. et al. Assessing the predictive accuracy of oral glucose effectiveness index using a calibration model. Endocrine 63, 391–397 (2019). https://doi.org/10.1007/s12020-018-1804-0

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  • DOI: https://doi.org/10.1007/s12020-018-1804-0

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