Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes?

Rong Liu, Katherine Kaufer Christoffel, Wendy J. Brickman, Xin Liu, Meghana Gadgil, Guoying Wang, Donald Zimmerman, Qi Chen, Binyan Wang, Zhiping Li, Houxun Xing, Xiping Xu, Xiaobin Wang

Research output: Contribution to journalArticle

Abstract

Aims: 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.

Original languageEnglish (US)
Pages (from-to)245-250
Number of pages6
JournalDiabetes Research and Clinical Practice
Volume105
Issue number2
DOIs
StatePublished - 2014

Fingerprint

Type 2 Diabetes Mellitus
Insulin Resistance
Glucose
ROC Curve
Fasting
Aptitude
Glucose Tolerance Test

Keywords

  • Adult
  • Chinese
  • Insulin resistance indices
  • Pre-diabetes
  • Predict
  • Type 2 diabetes

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Internal Medicine
  • Endocrinology

Cite this

Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes? / Liu, Rong; Christoffel, Katherine Kaufer; Brickman, Wendy J.; Liu, Xin; Gadgil, Meghana; Wang, Guoying; Zimmerman, Donald; Chen, Qi; Wang, Binyan; Li, Zhiping; Xing, Houxun; Xu, Xiping; Wang, Xiaobin.

In: Diabetes Research and Clinical Practice, Vol. 105, No. 2, 2014, p. 245-250.

Research output: Contribution to journalArticle

Liu, R, Christoffel, KK, Brickman, WJ, Liu, X, Gadgil, M, Wang, G, Zimmerman, D, Chen, Q, Wang, B, Li, Z, Xing, H, Xu, X & Wang, X 2014, 'Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes?', Diabetes Research and Clinical Practice, vol. 105, no. 2, pp. 245-250. https://doi.org/10.1016/j.diabres.2014.04.014
Liu, Rong ; Christoffel, Katherine Kaufer ; Brickman, Wendy J. ; Liu, Xin ; Gadgil, Meghana ; Wang, Guoying ; Zimmerman, Donald ; Chen, Qi ; Wang, Binyan ; Li, Zhiping ; Xing, Houxun ; Xu, Xiping ; Wang, Xiaobin. / Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes?. In: Diabetes Research and Clinical Practice. 2014 ; Vol. 105, No. 2. pp. 245-250.
@article{54d17d41508b425f880990d6c555ab98,
title = "Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes?",
abstract = "Aims: 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.",
keywords = "Adult, Chinese, Insulin resistance indices, Pre-diabetes, Predict, Type 2 diabetes",
author = "Rong Liu and Christoffel, {Katherine Kaufer} and Brickman, {Wendy J.} and Xin Liu and Meghana Gadgil and Guoying Wang and Donald Zimmerman and Qi Chen and Binyan Wang and Zhiping Li and Houxun Xing and Xiping Xu and Xiaobin Wang",
year = "2014",
doi = "10.1016/j.diabres.2014.04.014",
language = "English (US)",
volume = "105",
pages = "245--250",
journal = "Diabetes Research and Clinical Practice",
issn = "0168-8227",
publisher = "Elsevier Ireland Ltd",
number = "2",

}

TY - JOUR

T1 - Do static and dynamic insulin resistance indices perform similarly in predicting pre-diabetes and type 2 diabetes?

AU - Liu, Rong

AU - Christoffel, Katherine Kaufer

AU - Brickman, Wendy J.

AU - Liu, Xin

AU - Gadgil, Meghana

AU - Wang, Guoying

AU - Zimmerman, Donald

AU - Chen, Qi

AU - Wang, Binyan

AU - Li, Zhiping

AU - Xing, Houxun

AU - Xu, Xiping

AU - Wang, Xiaobin

PY - 2014

Y1 - 2014

N2 - Aims: 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.

AB - Aims: 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.

KW - Adult

KW - Chinese

KW - Insulin resistance indices

KW - Pre-diabetes

KW - Predict

KW - Type 2 diabetes

UR - http://www.scopus.com/inward/record.url?scp=84906046420&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84906046420&partnerID=8YFLogxK

U2 - 10.1016/j.diabres.2014.04.014

DO - 10.1016/j.diabres.2014.04.014

M3 - Article

C2 - 24882014

AN - SCOPUS:84906046420

VL - 105

SP - 245

EP - 250

JO - Diabetes Research and Clinical Practice

JF - Diabetes Research and Clinical Practice

SN - 0168-8227

IS - 2

ER -