The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees of β-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient β-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and β-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p < 0.0001), the fasting insulin concentration (Rs = 0.81, p < 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p < 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient β-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p < 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p < 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for β-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
β-cell function insulin resistance mathematical model intravenous glucose tolerance test glucose clamp insulin receptors Type 2 diabetes insulin glucose