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Using haemoglobin A1c to diagnose type 2 diabetes or to identify people at high risk of diabetes

BMJ 2014; 348 doi: (Published 25 April 2014) Cite this as: BMJ 2014;348:g2867

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Re: Using haemoglobin A1c to diagnose type 2 diabetes or to identify people at high risk of diabetes

The present article (1) has renewed the interest afresh in issues related to the usage of different methodological approaches in the diagnosis of diabetes. Diagnosis of diabetes has most commonly relied on the measurement of plasma (or blood or serum) glucose concentrations in timed samples, such as fasting glucose; in random or casual samples independent of prandial status; or after two hours of the 75-g oral glucose tolerance test (OGTT). These methods based on the measurement of blood has its own merits and demerits. The advantages are the easy availability of laboratory conducting the tests and low cost. The disadvantages are a) maintaining fasting before blood sampling, b) variability in the tests results between laboratories with low concordance of test results, c) Blood sampling more than one in case of 2 hour post prandial in addition to the inconvenience of the patient in taking glucose. In addition, there is lability of glucose in the collection tube at room temperature (2). It has been reported that even when whole blood samples are collected in sodium fluoride to inhibit in vitro glycolysis, storage at room by 1 to 4 hours before analysis leads to a decrease in glucose levels by 3–10 mg/dl in nondiabetic individuals (3).

Earlier expert group committee reports in 1997 recommended that the fasting plasma glucose (FPG) level, rather than the 2 hour plasma glucose level, be the preferred test to diagnose diabetes because of its convenience to patient, less cost, and superior repeat-test reproducibility (4). It has also been recommended that for impaired fasting glucose levels (IFG), oral glucose tolerance test (OGTT) should remain the “gold standard.” A follow-up report from the expert committee in 2003 refined the fasting glucose value range for IFG from ≥110 but <126 mg/dl to ≥100 but <126 mg/dl (≥6.1 but <7.0 mmol/l to ≥5.6 but <7.0 mmol/l) (5).

Over a period of time, since the first description of Glycated hemoglobin (HbA1c) by Rahbar et al in 1969 (6), it has been shown that the level of HbA1c correlated well with the glycemic control over a period of 2 to 3 months (7). This led to the gradual incorporation of the test into clinical practice in the 1980s. The correlation findings of the diabetes complications and the HbA1c levels by the United Kingdom Prospective Diabetes Study (8) has further strengthened the basis of HbA1c estimation as a cornerstone for diabetes management.

HbA1c is now universally accepted as an index of long-term glycemic control and there is increasing evidence in using HbA1c for the diagnosis of diabetes. The points in favour are: (a) its stability, measurement values not altered by fasting or post prandial states (9), (b) no need for fasting, (c) single sample of blood required, (d) better reflects the glycemic level over a 2-3 months period prior to the test, (e) standardized as compared to glucose, (f) less biological variability, (g) substantially less preanalytic instability, (h) relatively unaffected by acute (e.g., stress or illness related) perturbations in glucose levels , and (i) currently used to guide management and adjust therapy (10). With the availability of newer assays, many of the technical problems associated with the estimation of HbA1c has been removed.

The use of HbA1c as a diagnostic test has several limitations. There is no clear agreement on the cut off level. Studies have shown that there is high correlation between diabetic retinopathy and HbA1c levels >/ 6.5, and various organizations have proposed HbA1c targets of less than 6.5 to 7% to define good control of diabetes (11,12). Some factors such as genetic variants (e.g. HbS trait, HbC trait), elevated fetal hemoglobin (HbF) and chemically modified derivatives of hemoglobin (e.g. carbamylated Hb in patients with renal failure) can affect the accuracy of HbA1c measurements (13).

Any condition that shortens erythrocyte survival or decreases mean erythrocyte age (e.g., recovery from acute blood loss, hemolytic anemia) will falsely lower HbA1c test results regardless of the assay method used (14). Iron deficiency anemia is associated with higher HbA1c and higher fructosamine and iron replacement therapy lowers both HbA1c and fructosamine concentrations in diabetic and non-diabetic individuals (15).

Recent reports suggest that in chronic renal failure, HbA1c underestimates glycemic control in diabetic patients on dialysis and that glycated albumin is a more robust indicator of glycemic control (16,17,18).

Several drugs have been implicated with varying levels of HbA1c levels. Drugs that falsely lowers HbA1c levels include dapsone, ribavirin, antiretrovirals, trimethoprim-sulfamethoxazole, hydroxyurea, vitamin C, vitamin E etc. Drugs that falsely increase HbA1c levels include aspirin in high doses and chronic opiate use etc.

Despite these limitations, arguably HbA1c can be considered for diagnosis and let us look at the recommendations of the International Expert Committee on the diagnostic role of diabetes, which is shown below (10).

For the diagnosis of diabetes

•There is no single assay related to hyperglycemia that can be considered the gold standard, as it relates to the risk for microvascular or macrovascular complications.
•A measure that captures chronic glucose exposure is more likely to be informative regarding the presence of diabetes than is a single measure of glucose.
•The A1C assay provides a reliable measure of chronic glycemia and correlates well with the risk of long-term diabetes complications.
•The A1C assay (standardized and aligned with the Diabetes Control and Complications Trial/UK Prospective Diabetes Study assay) has several technical, including preanalytic and analytic, advantages over the currently used laboratory measurements of glucose.
•For the reasons above, the A1C assay may be a better means of diagnosing diabetes than measures of glucose levels.
•The diagnosis of diabetes is made if the A1C level is ≥6.5%. Diagnosis should be confirmed with a repeat A1C test unless clinical symptoms and glucose levels >200 mg/dl (>11.1 mmol/l) are present.
•If A1C testing is not possible owing to patient factors that preclude its interpretation (e.g., hemoglobinopathy or abnormal erythrocyte turnover) or to unavailability of the assay, previously recommended diagnostic measures (e.g., FPG and 2HPG) and criteria should be used. Mixing different methods to diagnose diabetes should be avoided.
•In children and adolescents, A1C testing is indicated when diabetes is suspected in the absence of the classical symptoms or a plasma glucose concentration >200 mg/dl (>11.1 mmol/l).
•The diagnosis of diabetes during pregnancy, when changes in red cell turnover make the A1C assay problematic, will continue to require glucose measurements.

For the identification of individuals at high risk for diabetes

•Individuals with an A1C level ≥6% but <6.5% are likely at the highest risk for progression to diabetes, but this range should not be considered an absolute threshold at which preventative measures are initiated.
•The classification of subdiabetic hyperglycemia as pre-diabetes is problematic because it suggests that all individuals so classified will develop diabetes and that individuals who do not meet these glycemia-driven criteria(regardless of other risk factor values) are unlikely to develop diabetes—neither of which is the case. Moreover, the categorical classification of individuals as high risk (e.g., IFG or IGT) or low risk, based on any measure of glycemia, is less than ideal because the risk for progression to diabetes appears to be a continuum. The glucose-related terms describing subdiabetic hyperglycemia will be phased out of use as clinical diagnostic states as A1C measurements replace glucose measurements for the diagnosis of diabetes.
•When assessing risk, implementing prevention strategies, or initiating a population-based prevention program, other diabetes risk factors should be taken into account. In addition, the A1C level at which to begin preventative measures should reflect the resources available, the size of the population affected, and the anticipated degree of success of the intervention. Further analyses of cost-benefit should guide the selection of high-risk groups targeted for intervention within specific populations.

In conclusion, it can be inferred that there is still a need for more evidence to get a clear cut off level value for HbA1c for diagnosis of diabetes. In developing countries with resource settings, blood glucose level estimation can be conveniently used and limitations of HbA1c needs to be considered before using HbA1c in population surveys, which may be a costly affair.


1. Using haemoglobin A1c to diagnose type 2 diabetes or to identify people at high risk of diabetes. BMJ 2014;348:g2867.

2. Murphy JM, Browne RW, Hill L, Bolelli GF, Abagnato C, Berrino F, Freudenheim J, Trevisan M, Muti P. Effects of transportation and delay in processing on the stability of nutritional and metabolic biomarkers. Nutr Cancer 2000; 37: 155– 160.

3. Bruns DE, Knowler WC. Stabilization of glucose in blood samples: why it matters. Clin Chem 2009; 55: 850– 852.

4. The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care 1997; 20: 1183– 1197.

5. The Expert Committee on the Diagnosis and Classification of Diabetes Mellitus Follow-up report on the diagnosis of diabetes mellitus. Diabetes Care 2003; 26: 3160– 3167.

6. Rahbar S, Blumenfeld O, Ranney HM. Studies of an unusual haemoglobin in patients with diabetes mellitus. Biochem Biophys Res Commun. 1969;36:838–43.

7. Gonen B, Rubenstein A, Rochman H, Tanega SP, Horwitz DL. D. Haemoglobin A1: An indicator of the metabolic control of diabetic patients. Lancet. 1977;2:734–7.

8. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood glucose control with sulfonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33) Lancet. 1998;352:837–53.

9. 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. The International Expert Committee. International Expert Committee report on the role of the A1c assay in the diagnosis of diabetes. Diabetes Care. 2009;32:1327–34.

11. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2012;35(Suppl 1):S11–63.

12. Rodbard HW, Jellinger PS, Davidson JA, Einhorn D, Garber AJ, Grunberger G et al. Statement by an American association of clinical endocrinologists/ american college of endocrinology consensus panel on type 2 diabetes mellitus: An algorithm for glycemic control. Endocr Pract. 2009;15:540–59.

13. Bry L, Chen PC, Sacks DB. Effects of hemoglobin variants and chemically modified derivatives on assays for glycated hemoglobin. Clin. Chem. 2001;47:153-63.

14. Goldstein DE, Little RR, Lorenz RA, Malone JI, Nathan D, Peterson CM: American Diabetes Association Technical Review on Tests of Glycemia. Diabetes Care 1995;18:896-909.

15. Sundaram RC, Selvaraj N, Vijayan G et al.: Increased plasma malondialdehyde and fructosamine in iron deficiency anemia: effect of treatment. Biomed Pharmacother 2007; 61:682-5.

16. Peacock TP, Shihabi ZK, Bleyer AJ et al.: Comparison of glycated albumin and hemoglobin A(1c) levels in diabetic subjects on hemodialysis. Kidney Int 2008;73:1062-8.

17. Inaba M,Glycated albumin is a better glycemic indicator than glycated hemoglobin values in hemodialysis patients with diabetes: effect of anemia and erythropoietin injection. J am Soc Nephrol 2007;18:896-903.

18. Freedman BI, Shihabi ZK, Andries L, Cardona CY, Peacock TP, Byers JR, Russell GB, Stratta RJ, Bleyer, AJ. Relationship between assays of glycemia in diabetic subjects with advanced chronic kidney disease. Am J Nephrol 2010;31:375-9.


Mongjam Meghachandra Singh
Department of Community Medicine
Maulana Azad Medical College, New Delhi

Reeta Devi
Assistant Professor,
School of Health Sciences,
Indira Gandhi National Open University, New Delhi

Vasu Saini
Ex-intern, Maulana Azad Medical College, New Delhi.

Competing interests: No competing interests

27 April 2014
Mongjam Meghachandra Singh
Reeta Devi, Vasu Saini
Maulana Azad Medical College, New Delhi; co-author- Indira Gandhi National Open University, New Delhi
Department of Community Medicine, Maulana Azad Medical College, New Delhi, India. Co-author : School of Health Sciences, IGNOU, New Delhi (India)