OBJECTIVE: In this study we compared fasting insulin and measures of insulin sensitivity (M) based on fasting insulin and glucose (i.e., homeostasis model assessment [HOMA], quantitative insulin sensitivity check index [QUICKI], and fasting glucose-to-insulin ratio [FGIR]) or triglycerides to the insulin clamp in a cohort of children/adolescents. RESEARCH DESIGN AND METHODS: The subjects were Minneapolis fifth- to eighth-grade students. Euglycemic-hyperinsulinemic clamps were performed on 323 adolescents at mean age 13 and were repeated on 300 of these subjects at mean age 15. Insulin sensitivity was determined by glucose uptake (milligrams per kilogram per minute) adjusted for lean body mass (M(LBM)) and steady-state insulin (M(LBM)/ln SSI). Comparisons were made for the whole cohort and by body size (BMI < 85th percentile vs. BMI > or = 85th percentile). Receiver operating characteristic (ROC) curves were used to test whether specific fasting insulin cut points separated true-positive from false-positive approximations of insulin resistance. RESULTS: Fasting insulin was significantly correlated with HOMA (r = 0.99), QUICKI (r = 0.79), FGIR (r = -0.62), and (ln fasting insulin + ln triglycerides) (r = 0.88). Correlations of the surrogates with M(LBM) were significantly lower than those with M for the total cohort and > or = 85th percentile group. In general, correlations in the > or = 85th percentile group were higher than those in the < 85th percentile group. Correlations with M(LBM) and M(LBM)/ln SSI decreased in the total cohort and > or = 85th percentile group from age 13 to 15. ROC curves showed only a modest capability to separate true- from false-positive values. CONCLUSIONS: Surrogate measures are only modestly correlated with the clamp measures of insulin sensitivity and do not offer any advantage over fasting insulin. In general, lower correlations are seen with M(LBM) than with M and with thinner than with heavier individuals.
OBJECTIVE: In this study we compared fasting insulin and measures of insulin sensitivity (M) based on fasting insulin and glucose (i.e., homeostasis model assessment [HOMA], quantitative insulin sensitivity check index [QUICKI], and fasting glucose-to-insulin ratio [FGIR]) or triglycerides to the insulin clamp in a cohort of children/adolescents. RESEARCH DESIGN AND METHODS: The subjects were Minneapolis fifth- to eighth-grade students. Euglycemic-hyperinsulinemic clamps were performed on 323 adolescents at mean age 13 and were repeated on 300 of these subjects at mean age 15. Insulin sensitivity was determined by glucose uptake (milligrams per kilogram per minute) adjusted for lean body mass (M(LBM)) and steady-state insulin (M(LBM)/ln SSI). Comparisons were made for the whole cohort and by body size (BMI < 85th percentile vs. BMI > or = 85th percentile). Receiver operating characteristic (ROC) curves were used to test whether specific fasting insulin cut points separated true-positive from false-positive approximations of insulin resistance. RESULTS: Fasting insulin was significantly correlated with HOMA (r = 0.99), QUICKI (r = 0.79), FGIR (r = -0.62), and (ln fasting insulin + ln triglycerides) (r = 0.88). Correlations of the surrogates with M(LBM) were significantly lower than those with M for the total cohort and > or = 85th percentile group. In general, correlations in the > or = 85th percentile group were higher than those in the < 85th percentile group. Correlations with M(LBM) and M(LBM)/ln SSI decreased in the total cohort and > or = 85th percentile group from age 13 to 15. ROC curves showed only a modest capability to separate true- from false-positive values. CONCLUSIONS: Surrogate measures are only modestly correlated with the clamp measures of insulin sensitivity and do not offer any advantage over fasting insulin. In general, lower correlations are seen with M(LBM) than with M and with thinner than with heavier individuals.
Authors: Kevin C Oeffinger; Beverley Adams-Huet; Ronald G Victor; Timothy S Church; Peter G Snell; Andrea L Dunn; Debra A Eshelman-Kent; Robert Ross; Peter M Janiszewski; Alicia J Turoff; Sandra Brooks; Gloria Lena Vega Journal: J Clin Oncol Date: 2009-06-29 Impact factor: 44.544
Authors: Julia Steinberger; Alan R Sinaiko; Aaron S Kelly; Wendy M Leisenring; Lyn M Steffen; Pamela Goodman; Daniel A Mulrooney; Andrew C Dietz; Antoinette Moran; Joanna L Perkins; K Scott Baker Journal: J Pediatr Date: 2011-09-13 Impact factor: 4.406
Authors: Cheril L Clarson; Farid H Mahmud; Janet E Baker; Helen E Clark; Wendy M McKay; Vicki D Schauteet; David J Hill Journal: Endocrine Date: 2009-04-23 Impact factor: 3.633