Publication

HOMA and Matsuda indices of insulin sensitivity: poor correlation with minimal model-based estimates of insulin sensitivity in longitudinal settings

Dec 4, 2013 · 3 authors · 3 topics

Abstract

Aims/hypothesis Little is known about the performance of surrogates in assessing changes in insulin sensitivity over time. This report compared updated HOMA of insulin sensitivity (HOMA2-%S) and the Matsuda index from OGTTs with minimal model-based estimates of insulin sensitivity (SI) from frequently sampled IVGTTs (FSIGTs) in longitudinal settings and cross-sectional settings. Methods Two longitudinal studies were used: one a natural observational study in which 338 individuals were followed for a median of 4 years; one a clinical treatment study in which 97 individuals received pioglitazone treatment and were followed for 1 year. Pairs of OGTTs and FSIGTs were performed at baseline and follow-up. Correlations were computed. Impact of measurement uncertainty was investigated through simulation studies. Results Correlations between HOMA2-%S and SI from baseline or follow-up data were in the range reported previously (0.61-0.69). By contrast, correlations for changes over time were only 0.35-0.39. The corresponding correlations between the Matsuda index and SI were 0.66-0.72 for cross-sectional data and 0.40-0.48 for longitudinal change. Correlations for changes were significantly lower than the cross-sectional correlations in both studies ( p <0.03). Simulation results demonstrated that the reduced correlations for change were not explained by error propagation, supporting a real limitation of surrogates to fully capture longitudinal changes in insulin sensitivity. Conclusions/interpretation HOMA and Matsuda indices derived from cross-sectional data should be used cautiously in assessing longitudinal changes in insulin sensitivity.

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Authors

Anny H. XiangRichard M. WatanabeThomas A. Buchanan

Topics

Diabetes, Cardiovascular Risks, and LipoproteinsDiabetes Management and ResearchAdipokines, Inflammation, and Metabolic Diseases

About

PublishedDec 4, 2013
TypeArticle
Citations43
References18

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