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

ABSTRACT: 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).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.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.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.

SUBMITTER: Liu R

PROVIDER: S-EPMC4138243 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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

Liu Rong R Christoffel Katherine Kaufer KK Brickman Wendy J WJ Liu Xin X Gadgil Meghana M Wang Guoying G Zimmerman Donald D Chen Qi Q Wang Binyan B Li Zhiping Z Xing Houxun H Xu Xiping X Wang Xiaobin X

Diabetes research and clinical practice 20140430 2

<h4>Aims</h4>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).<h4>Methods</h4>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 ...[more]

PMID: 24882014

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Project description:BackgroundThe mitogenic and growth-stimulatory effects of insulin-like growth factors appear to play a role in prostate carcinogenesis, yet any direct association of circulating insulin levels and risk of prostate cancer remains unclear.MethodsWe investigated the relationship of the level of serum insulin, glucose, and surrogate indices of insulin resistance (ie, the molar ratio of insulin to glucose and the homeostasis model assessment of insulin resistance [HOMA-IR]) to the development of prostate cancer in a case-cohort study within the Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study cohort of Finnish men. We studied 100 case subjects with incident prostate cancer and 400 noncase subjects without prostate cancer from the larger cohort. Fasting serum was collected 5-12 years before diagnosis. We determined insulin concentrations with a double-antibody immunochemiluminometric assay and glucose concentrations with a hexokinase assay. Multivariable logistic regression models estimated relative risks as odds ratios (ORs), and all statistical tests were two-sided.ResultsInsulin concentrations in fasting serum that was collected on average 9.2 years before diagnosis among case subjects were 8% higher than among noncase subjects, and the molar ratio of insulin to glucose and HOMA-IR were 10% and 6% higher, respectively, but these differences were not statistically significant. Among subjects in the second through fourth insulin quartiles, compared with those in the first quartile, increased insulin levels were associated with statistically significantly increased risks of prostate cancer (OR = 1.50, 95% confidence interval [CI] = 0.75 to 3.03; OR = 1.75, 95% CI = 0.86 to 3.56; and OR = 2.55, 95% CI = 1.18 to 5.51; for the second through fourth insulin quartiles, respectively; P(trend) = .02). A similar pattern was observed with the HOMA-IR (OR = 2.10, 95% CI = 1.03 to 4.26; P(trend) = .02) for the highest vs lowest quartiles. Risk varied inconsistently with glucose concentration (P(trend) = .38). A stronger association between insulin level and prostate cancer risk was observed among leaner men and among men who were less physically active at work. Crude prostate cancer incidence was 154 prostate cancers per 100 000 person-years in the lowest quartile of fasting serum insulin vs 394 prostate cancers per 100 000 person-years in the highest quartile.ConclusionElevated fasting levels of serum insulin (but not glucose) within the normal range appear to be associated with a higher risk of prostate cancer.

Dataset Information

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

Publications

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

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