Home The frequency of testing for glycated haemoglobin, HbA1c, is linked to the probability of achieving target levels in patients with suboptimally controlled diabetes mellitus
Article
Licensed
Unlicensed Requires Authentication

The frequency of testing for glycated haemoglobin, HbA1c, is linked to the probability of achieving target levels in patients with suboptimally controlled diabetes mellitus

  • Christopher J. Duff , Ivonne Solis-Trapala , Owen J. Driskell , David Holland , Helen Wright , Jenna L. Waldron , Clare Ford , Jonathan J. Scargill , Martin Tran , Fahmy W.F. Hanna , R. John Pemberton , Adrian Heald and Anthony A. Fryer ORCID logo EMAIL logo
Published/Copyright: October 2, 2018
Become an author with De Gruyter Brill
Submit Manuscript Author Information
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 57 Issue 2

Abstract

Background

We previously showed, in patients with diabetes, that >50% of monitoring tests for glycated haemoglobin (HbA1c) are outside recommended intervals and that this is linked to diabetes control. Here, we examined the effect of tests/year on achievement of commonly utilised HbA1c targets and on HbA1c changes over time.

Methods

Data on 20,690 adults with diabetes with a baseline HbA1c of >53 mmol/mol (7%) were extracted from Clinical Biochemistry Laboratory records at three UK hospitals. We examined the effect of HbA1c tests/year on (i) the probability of achieving targets of ≤53 mmol/mol (7%) and ≤48 mmol/mol (6.5%) in a year using multi-state modelling and (ii) the changes in mean HbA1c using a linear mixed-effects model.

Results

The probabilities of achieving ≤53 mmol/mol (7%) and ≤48 mmol/mol (6.5%) targets within 1 year were 0.20 (95% confidence interval: 0.19–0.21) and 0.10 (0.09–0.10), respectively. Compared with four tests/year, having one test or more than four tests/year were associated with lower likelihoods of achieving either target; two to three tests/year gave similar likelihoods to four tests/year. Mean HbA1c levels were higher in patients who had one test/year compared to those with four tests/year (mean difference: 2.64 mmol/mol [0.24%], p<0.001).

Conclusions

We showed that ≥80% of patients with suboptimal control are not achieving commonly recommended HbA1c targets within 1 year, highlighting the major challenge facing healthcare services. We also demonstrated that, although appropriate monitoring frequency is important, testing every 6 months is as effective as quarterly testing, supporting international recommendations. We suggest that the importance HbA1c monitoring frequency is being insufficiently recognised in diabetes management.

Keywords: diabetes mellitus; glycaemic target; glycated haemoglobin; monitoring; test utilisation
Corresponding author: Prof. Anthony A. Fryer, Department of Clinical Biochemistry, Keele University, Institute for Applied Clinical Sciences, University Hospitals of North Midlands, Newcastle Road, Stoke-on-Trent, Staffordshire ST4 6QG, UK, Phone: +44 1782 674245, Fax: +44 844 244 8602

Acknowledgments

We are grateful to the members of Diabetes U.K. (North Staffordshire Branch) for advice and feedback on the patient aspects of the study.

  1. Author contributions: O.J.D., I.S-T, C.J.D. and A.A.F. wrote the initial draft of the manuscript, performed the data analysis and provided clinical advice and critique from a clinical laboratory scientist perspective. I.S-T. developed the statistical modelling, conducted the statistical analysis, contributed to the interpretation of results and drafted the manuscript. J.L.W., J.J.S, and M.T. performed the data extraction from the three centres. H.W. supported data preparation for analysis. C.F. provided clinical advice and critique from a clinical laboratory scientist perspective. A.H. and F.W.H. provided clinical advice and critique from a clinical/research diabetologist perspective. R.J.P. provided a patient perspective and ensured the team had a patient-centred focus. All authors reviewed and edited the manuscript. A.A.F. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: The study was supported by a National Institute for Health Research Healthcare Scientist Fellowship award to O.J.D. (HCS/08/011, Funder Id: 10.13039/501100000659), supervised by A.A.F.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organisation played no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care 2018;41 Suppl 1:S1–153.10.2337/dc18-Sint01Search in Google Scholar PubMed

2. National Institute for Health and Clinical Excellence. Type 2 diabetes in adults: management (NG28). (Last updated: July 2016). https://www.nice.org.uk/guidance/ng28. Accessed: 11 May 2018.Search in Google Scholar

3. National Institute for Health and Clinical Excellence. Type 1 diabetes in adults: diagnosis and management (NG17). (Last updated: July 2016). https://www.nice.org.uk/guidance/ng17. Accessed: 11 May 2018.Search in Google Scholar

4. Akan P, Cimrin D, Ormen M, Kume T, Ozkaya A, Ergor G, et al. The inappropriate use of HbA1c testing to monitor glycaemia: is there evidence in laboratory data? J Eval Clin Pract 2007;13:21–4.10.1111/j.1365-2753.2006.00641.xSearch in Google Scholar PubMed

5. Lyon AW, Higgins T, Wesenberg JC, Tran DV, Cembrowski GS. Variation in frequency of haemoglobin A1c (HbA1c) testing: population studies used to assess compliance with clinical practice guidelines and use of HbA1c to screen for diabetes. J Diab Sci Technol 2009;3:411–7.10.1177/193229680900300302Search in Google Scholar PubMed PubMed Central

6. Laxmisan A, Vaughan-Sarrazin M, Cram P. Repeated hemoglobin A1C ordering in the VA health system. Am J Med 2011;124:342–9.10.1016/j.amjmed.2010.10.019Search in Google Scholar PubMed

7. Driskell OJ, Holland D, Hanna FW, Jones PW, Pemberton RJ, Tran M, et al. Inappropriate requesting of glycated hemoglobin (HbA1c) is widespread: assessment of prevalence, impact of national guidance, and practice-to-practice variability. Clin Chem 2012;58:906–15.10.1373/clinchem.2011.176487Search in Google Scholar PubMed

8. Pivovarov R, Albers DJ, Hripcsak G, Sepulveda JL, Elhadad N. Temporal trends of hemoglobin A1c testing. J Am Med Inform Assoc 2014;21:1038–44.10.1136/amiajnl-2013-002592Search in Google Scholar PubMed PubMed Central

9. McCoy RG, Van Houten HK, Ross JS, Montori VM, Shah ND. HbA1c overtesting and overtreatment among US adults with controlled type 2 diabetes, 2001–13: observational population based study. Br Med J 2015;351:h6138.10.1136/bmj.h6138Search in Google Scholar PubMed PubMed Central

10. Paul CL, Piterman L, Shaw JE, Kirby C, Barker D, Robinson J, et al. Patterns of type 2 diabetes monitoring in rural towns: how does frequency of HbA1c and lipid testing compare with existing guidelines? Aust J Rural Health 2016;24:371–7.10.1111/ajr.12283Search in Google Scholar PubMed

11. Driskell OJ, Holland D, Waldron JL, Ford C, Scargill JJ, Heald A, et al. Reduced testing frequency for glycated haemoglobin, HbA1c, is associated with deteriorating diabetic control. Diabetes Care 2014;37:2731–7.10.2337/dc14-0297Search in Google Scholar PubMed

12. Scargill JJ, Livingston M, Holland D, Duff CJ, Fryer AA, Heald AH. Monitoring thyroid function in patients on levothyroxine. Assessment of conformity to national guidance and variability in practice. Exp Clin Endocrinol Diabetes 2017;125:625–33.10.1055/s-0043-103018Search in Google Scholar PubMed

13. Parcero AF, Yaeger T, Bienkowski RS. Frequency of monitoring hemoglobin A1C and achieving diabetes control. J Prim Care Community Health 2011;2:205–8.10.1177/2150131911403932Search in Google Scholar PubMed

14. Phan TL, Hossain J, Lawless S, Werk LN. Quarterly visits with glycated hemoglobin monitoring: the sweet spot for glycemic control in youth with type 1 diabetes. Diabetes Care 2014;37:341–5.10.2337/dc13-0980Search in Google Scholar PubMed

15. Fu C, Ji L, Wang W, Luan R, Chen W, Zhan S, et al. Frequency of HbA1c monitoring was inversely associated with glycemic control of patients with type 2 diabetes mellitus. J Endocrinol Invest 2012;35:269–73.Search in Google Scholar

16. Loh TP, Tan KM, Saw S, Sethi SK. Glycated haemoglobin: what is the diagnostic yield at shortened testing intervals? Diabetes Res Clin Pract 2011;94:e40–2.10.1016/j.diabres.2011.07.034Search in Google Scholar PubMed

17. Kalbfleisch JD, Lawless JF. The analysis of panel data under a Markov assumption. J Am Statistical Assoc 1985;80:863–71.10.1080/01621459.1985.10478195Search in Google Scholar

18. R Core Team. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2016. https://www.R-project.org/. Accessed: 11 May 2018.Search in Google Scholar

19. Jackson CH. Multi-state models for panel data: the msm package for R. J Stat Softw 2011;38:1–29.10.18637/jss.v038.i08Search in Google Scholar

20. Bates D, Maechler M, Bolker B, Walker S. Fitting linear mixed-effects models using lme4. J Stat Softw 2015;67:1–48.10.18637/jss.v067.i01Search in Google Scholar

21. Anichini R, Cosimi S, Di Carlo A, Orsini P, De Bellis A, Seghieri G, et al. Gender difference in response predictors after 1-year exenatide therapy twice daily in type 2 diabetic patients: a real world experience. Diabetes Metab Syndr Obes 2013;6: 123–9.10.2147/DMSO.S42729Search in Google Scholar PubMed PubMed Central

22. Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) Study Research Group. Intensive Diabetes Treatment and Cardiovascular Outcomes in Type 1 Diabetes: The DCCT/EDIC Study 30-Year Follow-up. Diabetes Care 2016;39:686–93.10.2337/dc15-1990Search in Google Scholar PubMed PubMed Central

23. Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes. N Engl J Med 2008;359:1577–89.10.1056/NEJMoa0806470Search in Google Scholar PubMed

24. Gaede P, Lund-Andersen H, Parving HH, Pedersen O. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med 2008;358:580–91.10.1016/j.jvs.2008.04.035Search in Google Scholar

25. Mannucci E, Monami M, Dicembrini I, Piselli A, Porta M. Achieving HbA1c targets in clinical trials and in the real world: a systematic review and meta-analysis. J Endocrinol Invest 2014;37:477–95.10.1007/s40618-014-0069-6Search in Google Scholar PubMed

26. Balkau B, Calvi-Gries F, Freemantle N, Vincent M, Pilorget V, Home PD. Predictors of HbA1c over 4 years in people with type 2 diabetes starting insulin therapies: the CREDIT study. Diabetes Res Clin Pract 2015;108:432–40.10.1016/j.diabres.2015.02.034Search in Google Scholar PubMed

27. Virtue MA, Furne JK, Nuttall FQ, Levitt MD. Relationship between GHb concentration and erythrocyte survival determined from breath carbon monoxide concentration. Diabetes Care 2004;27:931–5.10.2337/diacare.27.4.931Search in Google Scholar PubMed

28. Lupescu A, Bissinger R, Goebel T. Enhanced suicidal erythrocyte death contributing to anemia in the elderly. Cell Physiol Biochem 2015;36:773–83.10.1159/000430137Search in Google Scholar PubMed

29. Stratton IM, Adler AI, Neil HA. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. Br Med J 2000;321:405–12.10.1136/bmj.321.7258.405Search in Google Scholar PubMed PubMed Central

30. Sood R, Sood A, Ghosh AK. Non-evidence-based variables affecting physicians’ test-ordering tendencies: a systematic review. Neth J Med 2007;65:167–77.Search in Google Scholar

31. Smellie WS, Galloway MJ, Chinn D, Gedling P. Is clinical practice variability the major reason for differences in pathology requesting patterns in general practice? J Clin Pathol 2002;55:312–4.10.1136/jcp.55.4.312Search in Google Scholar PubMed PubMed Central

32. Yasaitis LC, Bubolz T, Skinner JS, Chandra A. Local population characteristics and hemoglobin A1c testing rates among diabetic medicare beneficiaries. PLoS One 2014;9:e111119.10.1371/journal.pone.0111119Search in Google Scholar PubMed PubMed Central

33. Fryer AA, Smellie WS. Managing demand for laboratory tests: a laboratory toolkit. J Clin Pathol 2013;66:62–72.10.1136/jclinpath-2011-200524Search in Google Scholar PubMed

34. Svensson E, Baggesen LM, Thomsen RW, Lyngaa T, Pedersen L, Nørrelund H, et al. Patient-level predictors of achieving early glycaemic control in type 2 diabetes mellitus: a population-based study. Diabet Med 2016;33:1516–23.10.1111/dme.13184Search in Google Scholar PubMed

35. Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis, 2nd ed. Hoboken, NJ: Wiley, 2011.10.1002/9781119513469Search in Google Scholar

36. Glymour MM, Weuve J, Berkman LF, Kawachi I, Robins JM. When is baseline adjustment useful in analyses of change? An example with education and cognitive change. Am J Epidemiol 2005;162:267–78.10.1093/aje/kwi187Search in Google Scholar PubMed

Supplementary Material

The online version of this article offers supplementary material ((https://doi.org/10.1515/cclm-2018-0503).

Received: 2018-05-11
Accepted: 2018-09-04
Published Online: 2018-10-02
Published in Print: 2018-12-19

©2019 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Obituary
  3. Jillian Russyll (AKA Jill) Tate
  4. Editorial
  5. The long way to standardization of practices: HbA1c as archetypal example
  6. Reviews
  7. Secretory tumors of the pituitary gland: a clinical biochemistry perspective
  8. Thalassemia in the laboratory: pearls, pitfalls, and promises
  9. Opinion Paper
  10. Diagnostic biomarkers of muscle injury and exertional rhabdomyolysis
  11. General Clinical Chemistry and Laboratory Medicine
  12. Patient’s knowledge and awareness about the effect of the over-the-counter (OTC) drugs and dietary supplements on laboratory test results: a survey in 18 European countries
  13. National surveys on 15 quality indicators for the total testing process in clinical laboratories of China from 2015 to 2017
  14. Urinary albumin strip assay as a screening test to replace quantitative technology in certain conditions
  15. Cerebrospinal fluid free kappa light chains and kappa index perform equal to oligoclonal bands in the diagnosis of multiple sclerosis
  16. Different immunoreactivity of monomers and dimers makes automated free light chains assays not equivalent
  17. The utility of saliva testing in the estimation of uremic toxin levels in serum
  18. Determination of cannabinoids in oral fluid and urine of “light cannabis” consumers: a pilot study
  19. Moving from the second to the third generation Roche PTH assays: what are the consequences for clinical practice?
  20. Baseline hepcidin measurement in the differential diagnosis of anaemia for elderly patients and its correlation with the increment of transferrin saturation following an oral iron absorption test
  21. Reference Values and Biological Variations
  22. A multicenter study for the evaluation of the reference interval for TSH in Italy (ELAS TSH Italian Study)
  23. Cancer Diagnostics
  24. Urinary measurement of circulating tumor DNA for treatment monitoring and prognosis of metastatic colorectal cancer patients
  25. BCL2L12: a multiply spliced gene with independent prognostic significance in breast cancer
  26. Diabetes
  27. The global impact of the International Federation of Clinical Chemistry and Laboratory Medicine, Education and Management Division: engaging stakeholders and assessing HbA1c quality in a multicentre study across China
  28. The frequency of testing for glycated haemoglobin, HbA1c, is linked to the probability of achieving target levels in patients with suboptimally controlled diabetes mellitus
  29. Letters to the Editor
  30. Response to article by Caponi et al. about serum free light chains
  31. Response to Letter to the Editor about immunochemical measurement of urine free light chains
  32. Estimated GFR-specific 99th percentiles for high-sensitive cardiac troponin T based on the adjusted analytical change limit (adjACL) in hospitalized patients
  33. Perioperative heart-type fatty acid binding protein concentration cutoffs for the identification of severe acute kidney injury in patients undergoing cardiac surgery
  34. A peculiar reaction curve with dual spikes in absorbance during a total bilirubin assay in spite of accurate results induced by high M-protein concentration
  35. Extremely low high-density-lipoprotein cholesterol due to an unusual non-inherited cause: a case report
  36. A single-center performance evaluation of the fully automated iFlash anti-Müllerian hormone immunoassay
  37. Genetic polymorphisms and variants in the LDL receptor associated with familial hypercholesterolemia: cascade screening and identification of the variants 666C>A, 862G>A, 901G>A, and 919G>A of a Brazilian family
  38. Undetected paraganglioma by functional imaging techniques: case report
  39. A particular case of AML patient with the polymorphism G105G (rs11554137) and the missense mutation R132C in IDH1 gene
  40. Atypical “hairy cell-like” presentation of leukemic mantle cell lymphoma
  41. Evaluation of a rapid centrifugation step (4500 g for 2 min) in coagulation assays to monitor direct oral anticoagulants
https://doi.org/10.1515/cclm-2018-0503
Keywords for this article
diabetes mellitus; glycaemic target; glycated haemoglobin; monitoring; test utilisation

Articles in the same Issue

  1. Frontmatter
  2. Obituary
  3. Jillian Russyll (AKA Jill) Tate
  4. Editorial
  5. The long way to standardization of practices: HbA1c as archetypal example
  6. Reviews
  7. Secretory tumors of the pituitary gland: a clinical biochemistry perspective
  8. Thalassemia in the laboratory: pearls, pitfalls, and promises
  9. Opinion Paper
  10. Diagnostic biomarkers of muscle injury and exertional rhabdomyolysis
  11. General Clinical Chemistry and Laboratory Medicine
  12. Patient’s knowledge and awareness about the effect of the over-the-counter (OTC) drugs and dietary supplements on laboratory test results: a survey in 18 European countries
  13. National surveys on 15 quality indicators for the total testing process in clinical laboratories of China from 2015 to 2017
  14. Urinary albumin strip assay as a screening test to replace quantitative technology in certain conditions
  15. Cerebrospinal fluid free kappa light chains and kappa index perform equal to oligoclonal bands in the diagnosis of multiple sclerosis
  16. Different immunoreactivity of monomers and dimers makes automated free light chains assays not equivalent
  17. The utility of saliva testing in the estimation of uremic toxin levels in serum
  18. Determination of cannabinoids in oral fluid and urine of “light cannabis” consumers: a pilot study
  19. Moving from the second to the third generation Roche PTH assays: what are the consequences for clinical practice?
  20. Baseline hepcidin measurement in the differential diagnosis of anaemia for elderly patients and its correlation with the increment of transferrin saturation following an oral iron absorption test
  21. Reference Values and Biological Variations
  22. A multicenter study for the evaluation of the reference interval for TSH in Italy (ELAS TSH Italian Study)
  23. Cancer Diagnostics
  24. Urinary measurement of circulating tumor DNA for treatment monitoring and prognosis of metastatic colorectal cancer patients
  25. BCL2L12: a multiply spliced gene with independent prognostic significance in breast cancer
  26. Diabetes
  27. The global impact of the International Federation of Clinical Chemistry and Laboratory Medicine, Education and Management Division: engaging stakeholders and assessing HbA1c quality in a multicentre study across China
  28. The frequency of testing for glycated haemoglobin, HbA1c, is linked to the probability of achieving target levels in patients with suboptimally controlled diabetes mellitus
  29. Letters to the Editor
  30. Response to article by Caponi et al. about serum free light chains
  31. Response to Letter to the Editor about immunochemical measurement of urine free light chains
  32. Estimated GFR-specific 99th percentiles for high-sensitive cardiac troponin T based on the adjusted analytical change limit (adjACL) in hospitalized patients
  33. Perioperative heart-type fatty acid binding protein concentration cutoffs for the identification of severe acute kidney injury in patients undergoing cardiac surgery
  34. A peculiar reaction curve with dual spikes in absorbance during a total bilirubin assay in spite of accurate results induced by high M-protein concentration
  35. Extremely low high-density-lipoprotein cholesterol due to an unusual non-inherited cause: a case report
  36. A single-center performance evaluation of the fully automated iFlash anti-Müllerian hormone immunoassay
  37. Genetic polymorphisms and variants in the LDL receptor associated with familial hypercholesterolemia: cascade screening and identification of the variants 666C>A, 862G>A, 901G>A, and 919G>A of a Brazilian family
  38. Undetected paraganglioma by functional imaging techniques: case report
  39. A particular case of AML patient with the polymorphism G105G (rs11554137) and the missense mutation R132C in IDH1 gene
  40. Atypical “hairy cell-like” presentation of leukemic mantle cell lymphoma
  41. Evaluation of a rapid centrifugation step (4500 g for 2 min) in coagulation assays to monitor direct oral anticoagulants
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 18.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2018-0503/html?lang=en
Scroll to top button