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Licensed Unlicensed Requires Authentication Published by De Gruyter March 22, 2014

Changing from glucose to HbA1c for diabetes diagnosis: predictive values of one test and importance of analytical bias and imprecision

  • Aneta Aleksandra Nielsen EMAIL logo , Per Hyltoft Petersen , Anders Green , Cramer Christensen , Henry Christensen and Ivan Brandslund

Abstract

Background: In Denmark, the use of HbA1c in the diagnosis of diabetes was adopted from March 2012. We evaluated the change in the number of diabetes cases diagnosed by haemoglobin A1c (HbA1c) versus fasting venous plasma glucose (FPG), and estimated the influence of analytical variation and bias on the HbA1c-based prevalence of diabetes.

Methods: The study population constituted 4239 individuals not known to have diabetes randomly selected from all inhabitants aged 25–75 years in the former County of Vejle, Denmark. The number of undiagnosed patients with diabetes in the study population using FPG or HbA1c as the diagnostic criterion was estimated. Furthermore, changes in the analytical bias and coefficient of variation (CV) for HbA1c analysis were simulated and the effect on the number of diabetes cases was observed.

Results: Changing the diagnostic test from FPG to HbA1c reduced the number of patients with diabetes by approximately 46% based on one measurement. The predictive value of one test of HbA1c was 91% versus only 66% for one test of FPG. Analytical variation had a much greater impact on the number of patients with diabetes than bias. At a bias of 0%, an increase of CVanalytical from 2.7% to 3.7% increased the number of diabetes cases by 90%.

Conclusions: In the study population, the percentage of undiagnosed patients with diabetes aged 25–75 years was reduced from 3.6% (95% CI 3.0%–4.2%) based on one FPG measurement (FPG ≥7.0 mmol/L) to only 1.9% (95% CI 1.5%–2.3%) if the diagnosis of diabetes was based on the criterion of HbA1c ≥48 mmol/mol (6.5% DCCT).


Corresponding author: Aneta Aleksandra Nielsen, MSc, Department of Clinical Immunology and Biochemistry, Vejle Hospital, Kabbeltoft 25, 7100 Vejle, Denmark, Phone: +45 7940 6632, Fax: +45 7940 6853, E-mail:

References

1. Standards of medical care in diabetes – 2010. Diabetes Care 2010;33(Suppl 1):S11–61.10.2337/dc10-S011Search in Google Scholar PubMed PubMed Central

2. International Expert Committee report on the role of the A1C assay in the diagnosis of diabetes. Diabetes Care 2009;32:1327–34.10.2337/dc09-9033Search in Google Scholar PubMed PubMed Central

3. Notat vedrørende diagnostik af diabetes mellitus med HbA1c (Note on diagnosis of diabetes mellitus with HbA1c – translation from Danish). Available from: http://www.sst.dk/media/Planlaegning%20og%20kvalitet/Diabetes/Diagnosticering/DiagnosticeringType2Diabetes.ashx. Accessed on 2 February, 2013.Search in Google Scholar

4. Hoelzel W, Miedema K. Development of a reference system for the international standardization of HbA1c/glycohemoglobin determinations. J Int Fed Clin Chem 1996;9:62–4, 66–7.Search in Google Scholar

5. Jeppsson J-O, Kobold U, Barr J, Finke A, Hoelzel W, Hoshino T, et al. Approved IFCC reference method for the measurement of HbA1c in human blood. Clin Chem Lab Med 2002;40:78–89.Search in Google Scholar

6. Finke A, Kobold U, Hoelzel W, Weykamp C, Miedema K, Jeppsson JO. Preparation of a candidate primary reference material for the international standardisation of HbA1c determinations. Clin Chem Lab Med 1998;36:299–308.10.1515/CCLM.1998.051Search in Google Scholar PubMed

7. Consensus statement on the worldwide standardization of the hemoglobin A1C measurement: the American Diabetes Association, European Association for the Study of Diabetes, International Federation of Clinical Chemistry and Laboratory Medicine, and the International Diabetes Federation. Diabetes Care 2007;30:2399–400.10.2337/dc07-1752Search in Google Scholar PubMed

8. Hanas R, John G. 2010 consensus statement on the worldwide standardization of the hemoglobin A1C measurement. Diabetes Care 2010;33:1903–4.10.2337/dc10-0953Search in Google Scholar PubMed PubMed Central

9. Hoelzel W, Weykamp C, Jeppsson J-O, Miedema K, Barr JR, Goodall I, et al. IFCC reference system for measurement of hemoglobin A1c in human blood and the national standardization schemes in the United States, Japan, and Sweden: a method-comparison study. Clin Chem 2004;50:166–74.10.1373/clinchem.2003.024802Search in Google Scholar PubMed

10. Nordin G. Coefficient of variation for hemoglobin A1c results that are traceable to national glycohemoglobin standardization program must be distinguished from coefficient of variation for results traceable to International Federation of Clinical Chemistry and Laboratory Medicine. Diabetes Technol Ther 2011;13:1271–2.10.1089/dia.2011.0106Search in Google Scholar PubMed

11. Weykamp CW, Mosca A, Gillery P, Panteghini M. The analytical goals for hemoglobin A1c measurement in IFCC units and national glycohemoglobin standardization program units are different. Clin Chem 2011;57:1204–6.10.1373/clinchem.2011.162719Search in Google Scholar PubMed

12. Desirable biological variation database specifications – Westgard QC. Available from: http://www.westgard.com/biodatabase1.htm. Accessed on 27 November, 2012.Search in Google Scholar

13. Stahl M, Jørgensen LG, Hyltoft Petersen P, Brandslund I, de Fine Olivarius N, Borch-Johnsen K. Optimization of preanalytical conditions and analysis of plasma glucose. 1. Impact of the new WHO and ADA recommendations on diagnosis of diabetes mellitus. Scand J Clin Lab Invest 2001;61:169–79.10.1080/003655101300133612Search in Google Scholar PubMed

14. Little RR, Rohlfing CL, Tennill AL, Connolly S, Hanson S. Effects of sample storage conditions on glycated hemoglobin measurement: evaluation of five different high performance liquid chromatography methods. Diabetes Technol Ther 2007;9:36–42.10.1089/dia.2006.0055Search in Google Scholar PubMed

15. Rohlfing C, Wiedmeyer H-M, Little R, Grotz VL, Tennill A, England J, et al. Biological variation of glycohemoglobin. Clin Chem 2002;48:1116–8.10.1093/clinchem/48.7.1116Search in Google Scholar

16. Carlsen S, Petersen PH, Skeie S, Skadberg Ø, Sandberg S. Within-subject biological variation of glucose and HbA(1c) in healthy persons and in type 1 diabetes patients. Clin Chem Lab Med 2011;49:1501–7.10.1515/CCLM.2011.233Search in Google Scholar

17. Sacks DB, Arnold M, Bakris GL, Bruns DE, Horvath AR, Kirkman MS, et al. Guidelines and recommendations for laboratory analysis in the diagnosis and management of diabetes mellitus. Diabetes Care 2011;34:e61–99.10.2337/dc11-9998Search in Google Scholar

18. WHO/International Classification of Diseases 10th Revision. Available from: http://apps.who.int/classifications/icd10/browse/2010/en. Accessed on 11 April, 2012.Search in Google Scholar

19. Green A, Gustav P. Internal documentation. Research Unit of Clinical Epidemiology, University of Southern Denmark, Centre for National Clinical Databases, South.Search in Google Scholar

20. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987;40:373–83.10.1016/0021-9681(87)90171-8Search in Google Scholar

21. Dansk Institut for ekstern kvalitetssikring for laboratorier i sundhedssektoren (Quality assurance for laboratories in health care – translation from Danish). Available from: http://www.deks.dk/index1.html. Accessed on 22 January, 2013.Search in Google Scholar

22. International EQAS – Ensuring excellent results – Labquality. Available from: http://www.labquality.fi/eqa-eqas/. Accessed on 22 January, 2013.Search in Google Scholar

23. Kvalitetssikring af laboratoriemedicinske aktiviteter i almen praksis (Danish Society for General Practice – translation from Danish). Available from: http://www.dsam.dk/files/13/kvalitetssikring_og_kvalitetskrav_2010_ark.pdf. Accessed on 8 February, 2013.Search in Google Scholar

24. WHO: Global database on body mass index. Available from: http://apps.who.int/bmi/index.jsp?introPage=intro_3.html. Accessed on 1 August, 2012.Search in Google Scholar

25. Selvin E, Marinopoulos S, Berkenblit G, Rami T, Brancati FL, Powe NR, et al. Meta-analysis: glycosylated hemoglobin and cardiovascular disease in diabetes mellitus. Ann Intern Med 2004;141:421–31.10.7326/0003-4819-141-6-200409210-00007Search in Google Scholar PubMed

26. Blake GJ, Pradhan AD, Manson JE, Williams GR, Buring J, Ridker PM, et al. Hemoglobin A1c level and future cardiovascular events among women. Arch Intern Med 2004;164:757–61.10.1001/archinte.164.7.757Search in Google Scholar PubMed

27. Gao L, Matthews FE, Sargeant LA, Brayne C. An investigation of the population impact of variation in HbA1c levels in older people in England and Wales: from a population based multi-centre longitudinal study. BMC Public Health 2008;8:54.10.1186/1471-2458-8-54Search in Google Scholar PubMed PubMed Central

28. Stavelin A, Petersen PH, Sølvik U, Sandberg S. Internal quality control of prothrombin time in primary care: comparing the use of patient split samples with lyophilised control materials. Thromb Haemost 2009;102:593–600.10.1160/TH09-02-0082Search in Google Scholar PubMed

29. Røraas T, Petersen PH, Sandberg S. Confidence intervals and power calculations for within-person biological variation: effect of analytical imprecision, number of replicates, number of samples, and number of individuals. Clin Chem 2012;58:1306–13.10.1373/clinchem.2012.187781Search in Google Scholar PubMed

30. McCance DR, Hanson RL, Charles MA, Jacobsson LT, Pettitt DJ, Bennett PH, et al. Comparison of tests for glycated haemoglobin and fasting and two hour plasma glucose concentrations as diagnostic methods for diabetes. Br Med J 1994;308:1323–8.10.1136/bmj.308.6940.1323Search in Google Scholar PubMed PubMed Central

31. Petersen PH, Brandslund I, Jørgensen L, Stahl M, Olivarius ND, Borch-Johnsen K. Evaluation of systematic and random factors in measurements of fasting plasma glucose as the basis for analytical quality specifications in the diagnosis of diabetes. 3. Impact of the new WHO and ADA recommendations on diagnosis of diabetes mellitus. Scand J Clin Lab Invest 2001;61:191–204.Search in Google Scholar

32. Jørgensen LG, Stahl M, Brandslund I, Hyltoft Petersen P, Borch-Johnsen K, de Fine Olivarius N. Plasma glucose reference interval in a low-risk population. 2. Impact of the new WHO and ADA recommendations on the diagnosis of diabetes mellitus. Scand J Clin Lab Invest 2001;61:181–90.10.1080/003655101300133621Search in Google Scholar PubMed

33. Jørgensen LG, Brandslund I, Stahl M, Hyltoft Petersen P, Iversen S, Klitgaard N, et al. Upper reference limit, analytical quality specifications and clinical use of haemoglobin A1C. Scand J Clin Lab Invest 2002;62:609–22.10.1080/003655102764654349Search in Google Scholar PubMed

34. Pani LN, Korenda L, Meigs JB, Driver C, Chamany S, Fox CS, et al. Effect of aging on A1C levels in individuals without diabetes: evidence from the Framingham Offspring Study and the National Health and Nutrition Examination Survey 2001–2004. Diabetes Care 2008;31:1991–6.10.2337/dc08-0577Search in Google Scholar PubMed PubMed Central

35. Nathan DM, Kuenen J, Borg R, Zheng H, Schoenfeld D, Heine RJ. Translating the A1C assay into estimated average glucose values. Diabetes Care 2008;31:1473–8.10.2337/dc08-0545Search in Google Scholar PubMed PubMed Central

36. Davidson MB, Schriger DL, Peters AL, Lorber B. Relationship between fasting plasma glucose and glycosylated hemoglobin: potential for false-positive diagnoses of type 2 diabetes using new diagnostic criteria. JAMA 1999;281:1203–10.10.1001/jama.281.13.1203Search in Google Scholar PubMed

37. Glümer C, Jørgensen T, Borch-Johnsen K. Prevalences of diabetes and impaired glucose regulation in a Danish population: the Inter99 study. Diabetes Care 2003;26:2335–40.10.2337/diacare.26.8.2335Search in Google Scholar PubMed

38. Gusto G, Vol S, Born C, Balkau B, Lamy J, Bourderioux C, et al. [Age and sex variations of HbA(1C) in a French population without known diabetes aged 6 to 79 years]. Ann Biol Clin (Paris) 2011;69:545–53.Search in Google Scholar

39. Bernal-Lopez MR, Santamaría-Fernandez S, Lopez-Carmona D, Tinahones FJ, Mancera-Romero J, Peña-Jimenez D, et al. HbA(1c) in adults without known diabetes from southern Europe. Impact of the new diagnostic criteria in clinical practice. Diabet Med 2011;28:1319–22.10.1111/j.1464-5491.2011.03317.xSearch in Google Scholar PubMed

40. Cowie CC, Rust KF, Byrd-Holt DD, Gregg EW, Ford ES, Geiss LS, et al. Prevalence of diabetes and high risk for diabetes using A1C criteria in the U.S. population in 1988–2006. Diabetes Care 2010;33:562–8.10.2337/dc09-1524Search in Google Scholar PubMed PubMed Central

41. Hayes L, Hawthorne G, Unwin N. Undiagnosed diabetes in the over-60s: performance of the Association of Public Health Observatories (APHO) Diabetes Prevalence Model in a general practice. Diabet Med 2012;29:115–20.10.1111/j.1464-5491.2011.03389.xSearch in Google Scholar PubMed

42. Scientific Committee on Quality Assurance (VUK), Analysekvalitetskrav til HbA1c ved brug til diagnostik og monitorering af diabetes (Analytical Quality of HbA1c when used for diagnosis and monitoring of diabetes – translation from Danish), Available from: http://www.dskb.dk/media/documents/VUK%20HbA1c.doc. Accessed on 2 March, 2012.Search in Google Scholar

43. College of American Pathologists (CAP) GH2 Survey Data. Available from: http://www.ngsp.org/CAP/CAP12a.pdf. Accessed on 12 February, 2013.Search in Google Scholar

Received: 2013-5-7
Accepted: 2014-2-13
Published Online: 2014-3-22
Published in Print: 2014-7-1

©2014 by Walter de Gruyter Berlin/Boston

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