Experimental, epidemiological and clinical evidence implicates insulin resistance and its accompanying hyperinsulinaemia in the development of cancer, but the relative importance of these disturbances in cancer remains unclear. There are, however, theoretical mechanisms by which hyperinsulinaemia could amplify such growth-promoting effects as insulin may have, as well as the growth-promoting effects of other, more potent, growth factors. Hyperinsulinaemia may also induce other changes, particularly in the IGF (insulin-like growth factor) system, that could promote cell proliferation and survival. Several factors can independently modify both cancer risk and insulin resistance, including subclinical inflammation and obesity. The possibility that some of the effects of hyperinsulinaemia might then augment pro-carcinogenic changes associated with disturbances in these factors emphasizes how, rather than being a single causative factor, insulin resistance may be most usefully viewed as one strand in a network of interacting disturbances that promote the development and progression of cancer.

After more than 20 years, minimal model analysis of intravenous glucose tolerance test glucose and insulin concentrations continues to be widely employed in studies of insulin sensitivity and insulin resistance. Moreover, problems encountered in solving the minimal model equations continue to find new solutions. Bayesian techniques enable prior knowledge to be incorporated into parameter estimation routines. They offer particular advantages in the measurement of insulin sensitivity with the minimal model, and provide an elegant means of improving model identification success rates and parameter precision. This comment describes the study by Agbaje and colleagues in this issue of Clinical Science that exemplifies a new phase in the evolution of minimal model practice.

Minimal model analysis of glucose and insulin concentrations in the intravenous glucose tolerance test (IVGTT) has been widely used to obtain a measure of insulin sensitivity in humans. Issues of model validity and IVGTT protocol have been explored extensively. Less attention has been paid, however, to the computer programming protocol for estimating the model parameters (programming implementation). Minimal model analysis of data from an IVGTT protocol involving a high glucose dose (0.5 g/kg) and a reduced sample schedule, employed in healthy pre- or post-menopausal women, healthy men or men with coronary heart disease or chronic heart failure (20 in each group), was undertaken according to 12 different programming implementations using a commercially available model-equation-solving program. The ability of the program to arrive at an acceptable solution to the model equations gave a success rate of between 39% and 96%, depending on the implementation. Variation in basal glucose assignment significantly affected the magnitude of estimates of insulin sensitivity. The maximum modelling success rate was achieved by introduction of an imputed glucose measurement at 360 min from the glucose injection, taking the basal glucose level as the fasting glucose concentration, and overweighting the initial glucose measurement after a delay for mixing. Use of this implementation to analyse data from a study comparing insulin sensitivities obtained using the minimal model and a euglycaemic clamp reference gave a correlation of 0.80 ( P < 0.001) between the two methods. Straightforward variations in programming implementation, involving appropriate assignment of the basal glucose concentration and use of an imputed glucose measurement signifying re-establishment of basal glucose levels following the IVGTT, can considerably improve modelling success rate.

1. Simplified protocols for the measurement of insulin resistance will facilitate studies of this potentially important variable. 2. Using the euglycaemic clamp as the reference technique, we have assessed the validity of the insulin sensitivity index (inversely related to insulin resistance) obtained using a high-dose (500 mg/kg), unmodified intravenous glucose tolerance test with a 16 point sampling schedule and analysis using the minimal model of glucose disappearance. The two methods were compared in 10 clinically normal subjects and five patients with severe heart failure secondary to coronary heart disease. 3. The insulin sensitivity index of the minimal model was compared with four clamp-derived measures. Correlation coefficients of 0.72–0.92 ( P < 0.01− P < 0.001) were obtained between the two methods over a wide range of insulin sensitivity [model values 1.03–14.63 min −1 /(pmol/l) × 10 −5 ]. Patients with heart failure had the lowest measures of insulin sensitivity. 4. The high-dose, unmodified intravenous glucose tolerance test with minimal model analysis is a straightforward and economical clinical procedure and provides a valid measure of insulin sensitivity, in health and disease.