title: Individualized pharmacokinetic risk assessment for development of diabetes in high risk population.
abstract: OBJECTIVE
  The objective of this study is to propose a non-parametric pharmacokinetic prediction model that addresses the individualized risk of developing type-2 diabetes in subjects with family history of type-2 diabetes.
  
  
  METHODS
  All selected 191 healthy subjects had both parents as type-2 diabetic. Glucose was administered intravenously (0.5 g/kg body weight) and 13 blood samples taken at specified times were analyzed for plasma insulin and glucose concentrations. All subjects were followed for an average of 13-14 years for diabetic or normal (non-diabetic) outcome.
  
  
  RESULTS
  The new logistic regression model predicts the development of diabetes based on body mass index and only one blood sample at 90 min analyzed for insulin concentration. Our model correctly identified 4.5 times more subjects (54% versus 11.6%) predicted to develop diabetes and more than twice the subjects (99% versus 46.4%) predicted not to develop diabetes compared to current non-pharmacokinetic probability estimates for development of type-2 diabetes.
  
  
  CONCLUSIONS
  Our model can be useful for individualized prediction of development of type-2 diabetes in subjects with family history of type-2 diabetes. This improved prediction may be an important mediating factor for better perception of risk and may result in an improved intervention.
authors: Abbott Laboratories, Abbott Park, IL, USA.
authors: N
authors: N
authors: Gupta
authors: N H
authors: NH
authors: Al-Huniti
authors: P
authors: P
authors: Veng-Pedersen
mesh_terms: D000293:Adolescent; D000328:Adult; D001786:Blood Glucose / Q000378:metabolism; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology* / Q000235:genetics; D005260:Female; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000097:blood; D008297:Male; D008875:Middle Aged; D012016:Reference Values; D012044:Regression Analysis; D015203:Reproducibility of Results; D018570:Risk Assessment; D012307:Risk Factors; D018709:Statistics, Nonparametric
chemical_list: D001786:Blood Glucose; D007328:Insulin