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Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates
OBJECTIVE—We investigated how β-cell function and insulin sensitivity or resistance are affected by the type of blood sample collected or choice of insulin assay and homeostatis model assessment (HOMA) calculator (http://www.dtu.ox.ac.uk). RESEARCH DESIGN AND METHODS—Insulin was measured using 11 di...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
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American Diabetes Association
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2518363/ https://www.ncbi.nlm.nih.gov/pubmed/18535197 http://dx.doi.org/10.2337/dc08-0097 |
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author | Manley, Susan E. Luzio, Stephen D. Stratton, Irene M. Wallace, Tara M. Clark, Penelope M.S. |
author_facet | Manley, Susan E. Luzio, Stephen D. Stratton, Irene M. Wallace, Tara M. Clark, Penelope M.S. |
author_sort | Manley, Susan E. |
collection | PubMed |
description | OBJECTIVE—We investigated how β-cell function and insulin sensitivity or resistance are affected by the type of blood sample collected or choice of insulin assay and homeostatis model assessment (HOMA) calculator (http://www.dtu.ox.ac.uk). RESEARCH DESIGN AND METHODS—Insulin was measured using 11 different assays in serum and 1 assay in heparinized plasma. Fasting subjects with normoglycemia (n = 12), pre-diabetes, i.e., impaired fasting glucose or impaired glucose tolerance (n = 18), or type 2 diabetes (n = 67) were recruited. Patients treated with insulin or those who were insulin antibody–positive were excluded. HOMA estimates were calculated using specific insulin (SI) or radioimmunoassay (RIA) calculators (version 2.2). RESULTS—All glucose values were within model (HOMA) limits but not all insulin results, as 4.3% were <20 pmol/l and 1% were >300 pmol/l. β-Cell function derived from different insulin assays ranged from 67 to 122% (median) for those with normoglycemia (P = 0.026), from 89 to 138% for those with pre-diabetes (P = 0.990), and from 50 to 81% for those with type 2 diabetes (P < 0.0001). Furthermore, insulin resistance ranged from 0.8 to 2.0 (P = 0.0007), from 1.9 to 3.2 (P = 0.842), and from 1.5 to 2.9 (P < 0.0001), respectively. This twofold variation in HOMA estimates from the various insulin assays studied in serum may be significant metabolically. Insulin was 15% lower in heparinized plasma (used in the original HOMA study) compared with serum, which is now more commonly used. β-Cell function differed by 11% and insulin resistance by 15% when estimates derived from specific insulin were calculated using the RIA rather than the SI calculator. CONCLUSIONS—To enable comparison of HOMA estimates among individuals and different research studies, preanalytical factors and calculator selection should be standardized with insulin assays traceable to an insulin reference method procedure. |
format | Text |
id | pubmed-2518363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | American Diabetes Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-25183632009-09-01 Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates Manley, Susan E. Luzio, Stephen D. Stratton, Irene M. Wallace, Tara M. Clark, Penelope M.S. Diabetes Care Cardiovascular and Metabolic Risk OBJECTIVE—We investigated how β-cell function and insulin sensitivity or resistance are affected by the type of blood sample collected or choice of insulin assay and homeostatis model assessment (HOMA) calculator (http://www.dtu.ox.ac.uk). RESEARCH DESIGN AND METHODS—Insulin was measured using 11 different assays in serum and 1 assay in heparinized plasma. Fasting subjects with normoglycemia (n = 12), pre-diabetes, i.e., impaired fasting glucose or impaired glucose tolerance (n = 18), or type 2 diabetes (n = 67) were recruited. Patients treated with insulin or those who were insulin antibody–positive were excluded. HOMA estimates were calculated using specific insulin (SI) or radioimmunoassay (RIA) calculators (version 2.2). RESULTS—All glucose values were within model (HOMA) limits but not all insulin results, as 4.3% were <20 pmol/l and 1% were >300 pmol/l. β-Cell function derived from different insulin assays ranged from 67 to 122% (median) for those with normoglycemia (P = 0.026), from 89 to 138% for those with pre-diabetes (P = 0.990), and from 50 to 81% for those with type 2 diabetes (P < 0.0001). Furthermore, insulin resistance ranged from 0.8 to 2.0 (P = 0.0007), from 1.9 to 3.2 (P = 0.842), and from 1.5 to 2.9 (P < 0.0001), respectively. This twofold variation in HOMA estimates from the various insulin assays studied in serum may be significant metabolically. Insulin was 15% lower in heparinized plasma (used in the original HOMA study) compared with serum, which is now more commonly used. β-Cell function differed by 11% and insulin resistance by 15% when estimates derived from specific insulin were calculated using the RIA rather than the SI calculator. CONCLUSIONS—To enable comparison of HOMA estimates among individuals and different research studies, preanalytical factors and calculator selection should be standardized with insulin assays traceable to an insulin reference method procedure. American Diabetes Association 2008-09 /pmc/articles/PMC2518363/ /pubmed/18535197 http://dx.doi.org/10.2337/dc08-0097 Text en Copyright © 2008, DIABETES CARE Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details. |
spellingShingle | Cardiovascular and Metabolic Risk Manley, Susan E. Luzio, Stephen D. Stratton, Irene M. Wallace, Tara M. Clark, Penelope M.S. Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates |
title | Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates |
title_full | Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates |
title_fullStr | Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates |
title_full_unstemmed | Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates |
title_short | Preanalytical, Analytical, and Computational Factors Affect Homeostasis Model Assessment Estimates |
title_sort | preanalytical, analytical, and computational factors affect homeostasis model assessment estimates |
topic | Cardiovascular and Metabolic Risk |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2518363/ https://www.ncbi.nlm.nih.gov/pubmed/18535197 http://dx.doi.org/10.2337/dc08-0097 |
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