Monte Carlo analysis of a new model-based method for insulin sensitivity testing

Comput Methods Programs Biomed. 2008 Mar;89(3):215-25. doi: 10.1016/j.cmpb.2007.03.007.

Abstract

Insulin resistance (IR), or low insulin sensitivity, is a major risk factor in the pathogenesis of type 2 diabetes and cardiovascular disease. A simple, high resolution assessment of IR would enable earlier diagnosis and more accurate monitoring of intervention effects. Current assessments are either too intensive for clinical settings (Euglycaemic Clamp, IVGTT) or have too low resolution (HOMA, fasting glucose/insulin). Based on high correlation of a model-based measure of insulin sensitivity and the clamp, a novel, clinically useful test protocol is designed with: physiological dosing, short duration (<1 h), simple protocol, low cost and high repeatability. Accuracy and repeatability are assessed with Monte Carlo analysis on a virtual clamp cohort (N=146). Insulin sensitivity as measured by this test has a coefficient of variation (CV) of CV(SI)=4.5% (90% CI: 3.8-5.7%), slightly higher than clamp ISI (CV(ISI)=3.3% (90% CI: 3.0-4.0%)) and significantly lower than HOMA (CV(HOMA)=10.0% (90% CI: 9.1-10.8%)). Correlation to glucose and unit normalised ISI is r=0.98 (90% CI: 0.97-0.98). The proposed protocol is simple, cost effective, repeatable and highly correlated to the gold-standard clamp.

MeSH terms

  • Adult
  • Aged
  • Diabetes Mellitus, Type 2 / physiopathology*
  • Female
  • Humans
  • Insulin / metabolism*
  • Insulin Resistance*
  • Insulin Secretion
  • Male
  • Mass Screening*
  • Middle Aged
  • Models, Statistical
  • Monte Carlo Method
  • Risk Factors

Substances

  • Insulin