College of Pharmacy, University of Iowa, Iowa City, IA, USA.
J Pharmacokinet Pharmacodyn. 2011 Oct;38(5):563-79. doi: 10.1007/s10928-011-9208-2. Epub 2011 Aug 11.
Disease progression of type 2 diabetes (T2D) has received considerable attention, but little is known about the disease development of T2D. The purposes of this study were to identify disease development variables (DDV) for development of T2D and to compare corresponding models for disease development. All subjects included in this study were the offspring of diabetic parents and were followed up to 25 years. Repeated fasting blood samples were collected during the follow-up. Longitudinal data of four DDVs, namely fasting blood glucose (FBG), fasting serum insulin (FSI), homeostatic model assessment of insulin resistance (HOMA-IR) and body mass index (BMI) were recorded and compared. According to the diabetes status at the end of the follow-up, the data analysis involved a progressor group of 25 subjects, and a non-progressor group of 127 subjects. The temporal changes in the four DDVs over the time course of the disease development were evaluated by a single-slope and a dual-slope population-based Bayesian model. A dual-slope model based on FBG was found to be the best disease development model. For non-progressors, the FBG baseline stayed at 69.2 [66.5, 72.1] mg/dl (Bayes estimate [95% Bayesian credible set]) and increased with age by a rate of 0.227 mg/dl [0.149, 0.3] per year. For the progressors, the FBG increase with age the same rate as non-progressors and started to have an additional increase of 2.27 [0.505, 4.52] mg/dl per year, starting 8.73 [-10.8, -6.93] years before the diagnosis of T2D. No significant longitudinal increasing or decreasing temporal pattern was found for FSI, HOMA-IR and BMI by the population-based Bayesian approach. The proposed model, which enables a quantitative, time-based evaluation of the development of T2D in this higher risk population, may be used to quantify the effect of interventions/prevention strategies such as drug treatment and lifestyle changes.
2 型糖尿病（T2D）的疾病进展受到了广泛关注，但对于 T2D 的疾病发展过程知之甚少。本研究旨在确定 T2D 发展的疾病发展变量（DDV），并比较相应的疾病发展模型。本研究纳入的所有受试者均为糖尿病患者的子女，并随访 25 年。在随访期间采集多次空腹血样。记录并比较了四个 DDV，即空腹血糖（FBG）、空腹血清胰岛素（FSI）、稳态模型评估的胰岛素抵抗（HOMA-IR）和体重指数（BMI）的纵向数据。根据随访结束时的糖尿病状态，数据分析涉及进展组 25 例和非进展组 127 例。采用单斜率和双斜率基于人群的贝叶斯模型评估四个 DDV 在疾病发展过程中的时间变化。发现基于 FBG 的双斜率模型是最佳的疾病发展模型。对于非进展者，FBG 基线值保持在 69.2 [66.5，72.1] mg/dl（贝叶斯估计值[95%贝叶斯可信区间]），并随年龄以每年 0.227 mg/dl [0.149，0.3]的速度增加。对于进展者，FBG 随年龄增加的速度与非进展者相同，并开始以每年 2.27 [0.505，4.52] mg/dl的速度额外增加，在 T2D 诊断前 8.73 [-10.8，-6.93] 年开始。基于人群的贝叶斯方法未发现 FSI、HOMA-IR 和 BMI 的纵向增加或减少的时间模式。该模型可用于定量、基于时间的评估高危人群中 T2D 的发展，可用于量化药物治疗和生活方式改变等干预/预防策略的效果。
