Population insulin sensitivity from sparsely sampled oral glucose tolerance tests.

Objective: This work aimed to estimate population-level insulin sensitivity (S) from 2-hour oral glucose tolerance tests (OGTT) with less than 7 samples.

Research Design And Methods: The current methodology combines the OGTT mathematical model developed by Dalla Man et al., with nonlinear multilevel (NLML) statistical model to estimate population-level insulin sensitivity (S) from sparsely sampled datasets (3 or 4 samples per subject obtained in 120 min). To validate our novel methodology of population S estimation, we simulated 50 virtual subjects. We simulated 10 observations per subject over 240 minutes. After estimating their S using the OGTT model, the virtual subjects were split into two groups, subjects with S above the average and ones with below average. Subsequently, the simulated data were analyzed using statistical software and employing a t-test. The mean estimates of population S for the two groups of virtual subjects and their respective 95% CI were compared to the estimates obtained with our novel NLML group S estimates obtained using the 3 and 4 time points per subject. To further validate the performance of the novel NLML model, a set of 34 prediabetic and 30 diabetic subjects with T2D was used. As outlined above for the in-silico subjects, differences between the prediabetic and T2D subjects in regard to S was assessed using the classical two-stage approach (individual S estimation followed by statistical comparison of the two groups). The average estimates obtained with the classical two-stage approach were compared to the group estimated obtained with the NLML approach using 3 (0, 60, and 120 minutes) points per subject obtained in 120 minutes.

Results: Unique and identifiable individual estimates of S were obtained for all virtual subjects. In comparison to the subjects with above average S (n=25), the subjects with simulated below average S (n=25) exhibited significantly lower insulin sensitivity (P<0.001). Our novel NLML population model confirmed these findings (4-point OGTT: P<0.001; 3-point OGTT: P<0.001). In a similar fashion to the one outlined for the virtual subjects, the median insulin sensitivities estimated with the classical two-stage approach were different between the prediabetic (n=34) and T2D subjects (n=32, P=0.004). Using 3 points per subject, our novel NLML model confirmed these findings (P<0.001).

Conclusions: The population estimates of S from OGTT data is an effective tool to assess population insulin sensitivity and assess differences that may not be possible when calculating individual S or when less than 7 samples are available.