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. 2009 Mar;46(Pt 2):109-13.
doi: 10.1258/acb.2008.008160. Epub 2009 Jan 22.

Serum insulin-like growth factor binding protein-1: an improvement over other simple indices of insulin sensitivity in the assessment of subjects with normal glucose tolerance

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Serum insulin-like growth factor binding protein-1: an improvement over other simple indices of insulin sensitivity in the assessment of subjects with normal glucose tolerance

Anwar Borai et al. Ann Clin Biochem. 2009 Mar.

Abstract

Background: Insulin resistance is associated with an increased risk of cardiovascular disease and diabetes. It can be assessed using complex reference techniques, such as clamp or frequently sampled intravenous glucose tolerance test (FSIVGTT). Therefore, simple indices derived from fasting insulin and glucose concentrations have been proposed. The aim of this study is to assess fasting serum insulin-like growth factor binding protein-1 (IGFBP-1) as a simple index of insulin sensitivity compared with other simple indices and FSIVGTT.

Methods: Fasting serum IGFBP-1, fasting plasma insulin (FPI), homeostasis model assessment (HOMA-IR), quantitative insulin check index (QUICKI), fasting glucose to insulin ratio (FGIR), Raynaud and insulin glycaemic index (ISI-gly) were correlated with FSIVGTT (Si) in 22 subjects with normal glucose tolerance (NGT) and nine with impaired fasting glucose (IFG).

Results: In NGT individuals, IGFBP-1 correlated more strongly with Si than did any other index both before (r = 0.76) and after (r = 0.79) natural logarithm (ln) transformation. In subjects with IFG, IGFBP-1 was weakly correlated with Si before and after ln-transformation (r = 0.55, r = 0.56, respectively), but ISI-gly was the index most strongly correlated with Si (r = 0.77, r = 0.85, respectively).

Conclusions: In subjects with NGT, fasting serum IGFBP-1 could be used as a simple reliable marker of insulin sensitivity. For more accurate estimation of insulin sensitivity in normal subjects and those with IFG, ln-transformation is preferred over raw data.

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