title: Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes?
abstract: OBJECTIVE
  We designed a study to compare the predictive power of static and dynamic insulin resistance indices for categorized pre-diabetes (PDM)/type 2 diabetes (DM).
  
  
  METHODS
  Participants included 1134 adults aged 18-60 years old with normal glucose at baseline who completed both baseline and 6-years later follow-up surveys. Insulin resistance indices from baseline data were used to predict risk of PDM or DM at follow-up. Two static indices and two dynamic indices were calculated from oral glucose tolerance test results (OGTT) at baseline. Area under the receiver operating characteristic curve (AROC) analysis was used to estimate the predictive ability of candidate indices to predict PDM/DM. A general estimation equation (GEE) model was applied to assess the magnitude of association of each index at baseline with the risk of PDM/DM at follow-up.
  
  
  RESULTS
  The dynamic indices displayed the largest and statistically predictive AROC for PDM/DM diagnosed either by fasting glucose or by postprandial glucose. The bottom quartiles of the dynamic indices were associated with an elevated risk of PDM/DM vs. the top three quartiles. However, the static indices only performed significantly to PDM/DM diagnosed by fasting glucose.
  
  
  CONCLUSIONS
  Dynamic insulin resistance indices are stronger predictors of future PDM/DM than static indices. This may be because dynamic indices better reflect the full range of physiologic disturbances in PDM/DM.
authors.affiliation: Beijing An Zhen Hospital, Capital Medical University, The Key Laboratory of Remodeling-related Cardiovascular Diseases, Ministry of Education, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China; Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA. Electronic address: rongliu606@gmail.com.
authors.forename: Rong
authors.initials: R
authors.lastname: Liu
authors.affiliation: Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA.
authors.forename: Katherine Kaufer
authors.initials: KK
authors.lastname: Christoffel
authors.affiliation: Division of Endocrinology, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA.
authors.forename: Wendy J
authors.initials: WJ
authors.lastname: Brickman
authors.affiliation: Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA.
authors.forename: Xin
authors.initials: X
authors.lastname: Liu
authors.affiliation: Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Meghana
authors.initials: M
authors.lastname: Gadgil
authors.affiliation: Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA; Center on the Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
authors.forename: Guoying
authors.initials: G
authors.lastname: Wang
authors.affiliation: Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
authors.forename: Donald
authors.initials: D
authors.lastname: Zimmerman
authors.affiliation: Mary Ann and J. Milburn Smith Child Health Research Program, Department of Pediatrics, Northwestern University Feinberg School of Medicine and Ann & Robert H. Lurie Children's Hospital of Chicago and Children's Hospital of Chicago Research Center, Chicago, IL, USA.
authors.forename: Qi
authors.initials: Q
authors.lastname: Chen
authors.affiliation: Institute of Biomedicine, Anhui Medical University, Hefei, China.
authors.forename: Binyan
authors.initials: B
authors.lastname: Wang
authors.affiliation: Institute of Biomedicine, Anhui Medical University, Hefei, China.
authors.forename: Zhiping
authors.initials: Z
authors.lastname: Li
authors.affiliation: Institute of Biomedicine, Anhui Medical University, Hefei, China.
authors.forename: Houxun
authors.initials: H
authors.lastname: Xing
authors.affiliation: Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center, Key Lab for Organ Failure Research, Ministry of Education, Guangzhou, China.
authors.forename: Xiping
authors.initials: X
authors.lastname: Xu
authors.affiliation: Center on the Early Life Origins of Disease, Department of Population, Family and Reproductive Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA. Electronic address: xwang82@jhu.edu.
authors.forename: Xiaobin
authors.initials: X
authors.lastname: Wang
mesh_terms: D000293:Adolescent; D000328:Adult; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis*; D005215:Fasting / Q000502:physiology; D005260:Female; D005500:Follow-Up Studies; D005951:Glucose Tolerance Test; D006801:Humans; D007328:Insulin / Q000097:blood*; D007333:Insulin Resistance / Q000502:physiology; D008137:Longitudinal Studies; D008297:Male; D008875:Middle Aged; D019518:Postprandial Period / Q000502:physiology; D011236:Prediabetic State / Q000175:diagnosis*; D012372:ROC Curve; D012044:Regression Analysis; D055815:Young Adult
chemical_list: D007328:Insulin
keywords: Adult; Chinese; Insulin resistance indices; Pre-diabetes; Predict; Type 2 diabetes