Impact of demographics and disease progression on the relationship between glucose and HbA1c.

CONTEXT: Several studies have shown that the relationship between mean plasma glucose (MPG) and glycated haemoglobin (HbA1c) may vary across populations. Especially race has previously been referred to shift the regression line that links MPG to HbA1c at steady-state (Herman & Cohen, 2012). OBJECTIVE: To assess the influence of demographic and disease progression-related covariates on the intercept of the estimated linear MPG-HbA1c relationship in a longitudinal model. DATA: Longitudinal patient-level data from 16 late-phase trials in type 2 diabetes with a total of 8927 subjects was used to study covariates for the relationship between MPG and HbA1c. The analysed covariates included age group, BMI, gender, race, diabetes duration, and pre-trial treatment. Differences between trials were taken into account by estimating a trial-to-trial variability component. PARTICIPANTS: Participants included 47% females and 20% above 65years. 77% were Caucasian, 9% were Asian, 5% were Black and the remaining 9% were analysed together as other races. ANALYSIS: Estimates of the change in the intercept of the MPG-HbA1c relationship due to the mentioned covariates were determined using a longitudinal model. RESULTS: The analysis showed that pre-trial treatment with insulin had the most pronounced impact associated with a 0.34% higher HbA1c at a given MPG. However, race, diabetes duration and age group also had an impact on the MPG-HbA1c relationship. CONCLUSION: Our analysis shows that the relationship between MPG and HbA1c is relatively insensitive to covariates, but shows small variations across populations, which may be relevant to take into account when predicting HbA1c response based on MPG measurements in clinical trials.

Ethnic differences in insulin sensitivity, ß-cell function, and hepatic extraction between Japanese and Caucasians: a minimal model analysis.

CONTEXT: Ethnic differences have previously been reported for type 2 diabetes. OBJECTIVE: We aimed at assessing the potential differences between Caucasian and Japanese subjects ranging from normal glucose tolerance (NGT) to impaired glucose tolerance (IGT) and to type 2 diabetes. DESIGN: This was a cross-sectional study with oral glucose tolerance tests to assess ß-cell function, hepatic insulin extraction, and insulin sensitivity. PARTICIPANTS: PARTICIPANTS included 120 Japanese and 150 Caucasian subjects. MAIN OUTCOMES: Measures of ß-cell function, hepatic extraction, and insulin sensitivity were assessed using C-peptide, glucose, and insulin minimal models. RESULTS: Basal ß-cell function (Φ(b)) was lower in Japanese compared with Caucasians (P < .01). In subjects with IGT, estimates of the dynamic (Φ(d)) and static (Φ(s)) ß-cell responsiveness were significantly lower in the Japanese compared with Caucasians (P < .05). In contrast, values of insulin action showed higher sensitivity in the Japanese IGT subjects. Hepatic extraction was similar in NGT and IGT groups but higher in Japanese type 2 diabetic subjects (P < .01). Despite differences in insulin sensitivity, ß-cell function, and hepatic extraction, the disposition indices were similar between the 2 ethnic groups at all glucose tolerance states. Furthermore, the overall insulin sensitivity and ß-cell responsiveness for all glucose tolerance states were similar in Japanese and Caucasians after accounting for differences in body mass index. CONCLUSION: Our study provides evidence for a similar ability of Japanese and Caucasians to compensate for increased insulin resistance.

Body composition is the main determinant for the difference in type 2 diabetes pathophysiology between Japanese and Caucasians.

OBJECTIVE This cross-sectional clinical study compared the pathophysiology of type 2 diabetes in Japanese and Caucasians and investigated the role of demographic, genetic, and lifestyle-related risk factors for insulin resistance and ß-cell response. RESEARCH DESIGN AND METHODS A total of 120 Japanese and 150 Caucasians were enrolled to obtain comparable distributions of high/low BMI values across glucose tolerance states (normal glucose tolerance, impaired glucose tolerance, and type 2 diabetes), which were assessed by oral glucose tolerance tests. BMI in the two cohorts was distributed around the two regional cutoff values for obesity. RESULTS Insulin sensitivity was higher in Japanese compared with Caucasians, as indicated by the homeostatic model assessment of insulin resistance and Matsuda indices, whereas ß-cell response was higher in Caucasians, as measured by homeostatic model assessment of ß-cell function, the insulinogenic indices, and insulin secretion ratios. Disposition indices were similar for Japanese and Caucasians at all glucose tolerance states, indicating similar ß-cell response relative to the degree of insulin resistance. The main determinants for differences in metabolic indices were measures of body composition, such as BMI and distribution of adipose tissue. Differences in ß-cell response between Japanese and Caucasians were not statistically significant following adjustment by differences in BMI. CONCLUSIONS Our study showed similar disposition indices in Japanese and Caucasians and that the major part of the differences in insulin sensitivity and ß-cell response between Japanese and Caucasians can be explained by differences in body composition.

Mechanism-based population modelling for assessment of L-cell function based on total GLP-1 response following an oral glucose tolerance test.

GLP-1 is an insulinotropic hormone that synergistically with glucose gives rise to an increased insulin response. Its secretion is increased following a meal and it is thus of interest to describe the secretion of this hormone following an oral glucose tolerance test (OGTT). The aim of this study was to build a mechanism-based population model that describes the time course of total GLP-1 and provides indices for capability of secretion in each subject. The goal was thus to model the secretion of GLP-1, and not its effect on insulin production. Single 75 g doses of glucose were administered orally to a mixed group of subjects ranging from healthy volunteers to patients with type 2 diabetes (T2D). Glucose, insulin, and total GLP-1 concentrations were measured. Prior population data analysis on measurements of glucose and insulin were performed in order to estimate the glucose absorption rate. The individual estimates of absorption rate constants were used in the model for GLP-1 secretion. Estimation of parameters was performed using the FOCE method with interaction implemented in NONMEM VI. The final transit/indirect-response model obtained for GLP-1 production following an OGTT included two stimulation components (fast, slow) for the zero-order production rate. The fast stimulation was estimated to be faster than the glucose absorption rate, supporting the presence of a proximal-distal loop for fast secretion from L: -cells. The fast component (st3) = 8.64·10⁻5 [mg⁻¹]) was estimated to peak around 25 min after glucose ingestion, whereas the slower component (st4 = 26.2·10⁻5 [mg⁻¹]) was estimated to peak around 100 min. Elimination of total GLP-1 was characterised by a first-order loss. The individual values of the early phase GLP-1 secretion parameter (st3) were correlated (r = 0.52) with the AUC(0-60 min.) for GLP-1. A mechanistic population model was successfully developed to describe total GLP-1 concentrations over time observed after an OGTT. The model provides indices related to different mechanisms of subject abilities to secrete GLP-1. The model provides a good basis to study influence of different demographic factors on these components, presented mainly by indices of the fast- and slow phases of GLP-1 response.

Predictive performance for population models using stochastic differential equations applied on data from an oral glucose tolerance test.

Several articles have investigated stochastic differential equations (SDEs) in PK/PD models, but few have quantitatively investigated the benefits to predictive performance of models based on real data. Estimation of first phase insulin secretion which reflects beta-cell function using models of the OGTT is a difficult problem in need of further investigation. The present work aimed at investigating the power of SDEs to predict the first phase insulin secretion (AIR (0-8)) in the IVGTT based on parameters obtained from the minimal model of the OGTT, published by Breda et al. (Diabetes 50(1):150-158, 2001). In total 174 subjects underwent both an OGTT and a tolbutamide modified IVGTT. Estimation of parameters in the oral minimal model (OMM) was performed using the FOCE-method in NONMEM VI on insulin and C-peptide measurements. The suggested SDE models were based on a continuous AR(1) process, i.e. the Ornstein-Uhlenbeck process, and the extended Kalman filter was implemented in order to estimate the parameters of the models. Inclusion of the Ornstein-Uhlenbeck (OU) process caused improved description of the variation in the data as measured by the autocorrelation function (ACF) of one-step prediction errors. A main result was that application of SDE models improved the correlation between the individual first phase indexes obtained from OGTT and AIR (0-8) (r = 0.36 to r = 0.49 and r = 0.32 to r = 0.47 with C-peptide and insulin measurements, respectively). In addition to the increased correlation also the properties of the indexes obtained using the SDE models more correctly assessed the properties of the first phase indexes obtained from the IVGTT. In general it is concluded that the presented SDE approach not only caused autocorrelation of errors to decrease but also improved estimation of clinical measures obtained from the glucose tolerance tests. Since, the estimation time of extended models was not heavily increased compared to basic models, the applied method is concluded to have high relevance not only in theory but also in practice.