Defining the Relationship Between Plasma Glucose and HbA1c
Abstract
OBJECTIVE— To define the relationship between HbA1c and plasma glucose (PG) levels in patients with type 1 diabetes using data from the Diabetes Control and Complications Trial (DCCT). RESEARCH DESIGN AND METHODS— The DCCT was a multicenter, randomized clinical trial designed to compare intensive and conventional therapies and their relative effects on the development and progression of diabetic complications in patients with type 1 diabetes. Quarterly HbA1c and corresponding seven-point capillary blood glucose profiles (premeal, postmeal, and bedtime) obtained in the DCCT were analyzed to define the relationship between HbA1c and PG. Only data from complete profiles with corresponding HbA1c were used (n = 26,056). Of the 1,441 subjects who participated in the study, 2 were excluded due to missing data. Mean plasma glucose (MPG) was estimated by multiplying capillary blood glucose by 1.11. Linear regression analysis weighted by the number of observations per subject was used to correlate MPG and HbA1c. RESULTS— Linear regression analysis, using MPG and HbA1c summarized by patient (n = 1,439), produced a relationship of MPG (mmol/l) = (1.98 ○1 HbA1c) - 4.29 or MPG (mg/dl) = (35.6 ○1 HbA1c) - 77.3, r = 0.82). Among individual time points, afternoon and evening PG (postlunch, predinner, postdinner, and bedtime) showed higher correlations with HbA1c than the morning time points (prebreakfast, postbreakfast, and prelunch). CONCLUSIONS— We have defined the relationship between HbA1c and PG as assessed in the DCCT. Knowing this relationship can help patients with diabetes and their healthcare providers set day-to-day targets for PG to achieve specific HbA1c goals.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
To exclude invalid self-reported HbA1c data, users with a greater or less than 2.0% difference between self-reported HbA1c and 90-day mean blood glucose were excluded (n=44).
“To exclude invalid self-reported HbA1c data, we used the formula HbA1c=(90-day mean blood glucose + 77.3)/35.6 [11] to compare self-reported HbA1c to 90-day mean blood glucose, and excluded users with a greater or less than 2.0% difference (n=44 were excluded).”
From One drop | Mobile on iPhone and apple watch: an evaluation of hbA1c improvement associated with tracking self-care (2017) · cites this paper as [11]
Glycosylated hemoglobin reflects long-term glycemic control and is a more accurate and stable measure than fasting plasma glucose.
“Glycosylated hemoglobin reflects long-term glycemic control and is a more accurate and stable measure than FPG levels [13,14].”
From A Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults (2015) · cites this paper as [14]
The optimal cutoff values for HbA1c have been intensively reported in previous studies and discussed in several review papers.
“The optimal cutoff values for HbA1c has been intensively reported in previous studies and discussed in several review papers [4,14,15,38,41,42,43,44,45].”
From A Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults (2015) · cites this paper as [14]
There is substantial interindividual variation in A1C at the same levels of glycemia.
“Moreover, there is substantial interindividual variation in A1C at the same levels of glycemia (20,21), reflecting differences in red cell penetration, glycation, hemoglobin species, red cell half-life, vitamin and medication status, and others factors (22).”
From Screening for Diabetes and Pre-Diabetes With Proposed A1C-Based Diagnostic Criteria (2010) · cites this paper as [21]
Cites
(1993) · New England Journal of Medicine · doi:10.1056/nejm199309303291401 · Cited by 24,667 · see citing works
The Clinical Information Value of the Glycosylated Hemoglobin Assay
Nathan, D. M., Singer, D. E., Hurxthal, K., & Goodson, J. D. (1984) · New England Journal of Medicine · doi:10.1056/nejm198402093100602 · Cited by 706 · see citing works
Tai, M. (1994) · Diabetes Care · doi:10.2337/diacare.17.2.152 · Cited by 498 · see citing works
(1987) · Diabetes Care · doi:10.2337/diacare.10.1.1 · Cited by 485 · see citing works
Avignon, A., Radauceanu, A., & Monnier, L. (1997) · Diabetes Care · doi:10.2337/diacare.20.12.1822 · Cited by 363 · see citing works
MICA Polymorphism Is Associated With Type 1 Diabetes in the Korean Population
Park, Y.-S., Lee, H.-K., Sanjeevi, C. B., & Eisenbarth, G. S. (2001) · Diabetes Care · doi:10.2337/diacare.24.1.33 · Cited by 165 · see citing works
Unexplained variability of glycated haemoglobin in non-diabetic subjects not related to glycaemia
Yudkin, J. S., Forrest, R. D., Jackson, C. A., Ryle, A., Davie, S. J., & GOULD, B. J. (1990) · Diabetologia · doi:10.1007/bf00404798 · Cited by 154 · see citing works
Svendsen, P. A., Lauritzen, T., S�egaard, U., & Nerup, J. (1982) · Diabetologia · doi:10.1007/bf00260951 · Cited by 143 · see citing works
The Response of GHb to Stepwise Plasma Glucose Change Over Time in Diabetic Patients
Tahara, Y., & Shima, K. (1993) · Diabetes Care · doi:10.2337/diacare.16.9.1313 · Cited by 139 · see citing works
Neeley, W. E. (1972) · Clinical Chemistry · doi:10.1093/clinchem/18.6.509 · Cited by 136 · see citing works
Biological Variation of Glycated Hemoglobin: Implications for diabetes screening and monitoring
Kilpatrick, E. S., Maylor, P. W., & Keevil, B. G. (1998) · Diabetes Care · doi:10.2337/diacare.21.2.261 · Cited by 135 · see citing works
Standards of Medical Care for Patients With Diabetes Mellitus
(2002) · Clinical Diabetes · doi:10.2337/diaclin.20.1.24 · Cited by 94 · see citing works
Proposal for standardizing direct-reading biosensors for blood glucose
Fogh‐Andersen, N., & D’Orazio, P. (1998) · Clinical Chemistry · doi:10.1093/clinchem/44.3.655 · Cited by 84 · see citing works
Hudson, P. R., Child, D. F., Jones, H., & Williams, C. P. (1999) · Annals of Clinical Biochemistry International Journal of Laboratory Medicine · doi:10.1177/000456329903600408 · Cited by 61 · see citing works
Dunn, P. J., Cole, R., & Soeldner, J. S. (1979) · Metabolism · doi:10.1016/0026-0495(79)90185-9 · Cited by 52 · see citing works
What's ahead in glucose monitoring?
Bode, B. W., Sabbah, H. T., & Davidson, P. C. (2001) · Postgraduate Medicine · doi:10.3810/pgm.2001.04.906 · Cited by 29 · see citing works
Thel, M. C., & Harrington, R. A. (2008) · Springer eBooks · doi:10.1007/978-0-585-33754-8_44 · Cited by 13 · see citing works
Mosca, A., Carpinelli, A., & Bonini, P. A. (1986) · Clinical Chemistry · doi:10.1093/clinchem/32.1.202 · Cited by 13 · see citing works
Glucosebestimmung in hämolysierten Blutproben
Schlebusch, H., Sorger, M., Munz, E., et al. (1980) · Clinical Chemistry and Laboratory Medicine (CCLM) · doi:10.1515/cclm.1980.18.12.885 · Cited by 1 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Standards of medical care in diabetes—2014
American Diabetes Association (2014) · Diabetes Care · doi:10.2337/dc14-s014 · Cited by 4,572 · see citing works
Standards of medical care in diabetes—2013
American Diabetes Association (2013) · Diabetes Care · doi:10.2337/dc13-s011 · Cited by 4,369 · see citing works
Standards of medical care in diabetes 2010
American Diabetes Association (2010) · Diabetes Care · doi:10.2337/dc10-s011 · Cited by 3,470 · see citing works
Standards of medical care in diabetes—2011
American Diabetes Association (2011) · Diabetes Care · doi:10.2337/dc11-s011 · Cited by 2,880 · see citing works
Standards of Medical Care in Diabetes—2009
American Diabetes Association (2009) · Diabetes Care · doi:10.2337/dc09-s013 · Cited by 2,167 · see citing works
Translating the A1C assay into estimated average glucose values
Nathan, D. M., Kuenen, J., Borg, R., Zheng, H., Schoenfeld, D., Heine, R. J., & for the A1c-Derived Average Glucose (ADAG) Study Group (2008) · Diabetes Care · doi:10.2337/dc08-0545 · Cited by 1,812 · see citing works
Meta-analysis: glycosylated hemoglobin and cardiovascular disease in diabetes mellitus
Selvin, E., Marinopoulos, S., Berkenblit, G., Rami, T., Brancati, F. L., Powe, N. R., & Golden, S. H. (2004) · Annals of Internal Medicine · doi:10.7326/0003-4819-141-6-200409210-00007 · Cited by 1,657 · see citing works
Monnier, L., Lapinski, H., & Colette, C. (2003) · Diabetes Care · doi:10.2337/diacare.26.3.881 · Cited by 1,461 · see citing works
Standards of Medical Care in Diabetes—2008
American Diabetes Association (2008) · Diabetes Care · doi:10.2337/dc08-s012 · Cited by 1,377 · see citing works
Switching from insulin to oral sulfonylureas in patients with diabetes due to Kir6.2 mutations
Pearson, E. R., Flechtner, I., Njølstad, P. R., Malecki, M. T., Flanagan, S. E., Larkin, B., Ashcroft, F. M., Klimes, I., Codner, E., Iotova, V., et al. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa061759 · Cited by 988 · see citing works
Postprandial Hyperglycemia and Diabetes Complications
Ceriello, A. (2005) · Diabetes · doi:10.2337/diabetes.54.1.1 · Cited by 945 · see citing works
Surrogate markers of insulin resistance: A review
Singh, B. (2010) · World Journal of Diabetes · doi:10.4239/wjd.v1.i2.36 · Cited by 622 · see citing works
Metabolic Syndrome, Aging and Involvement of Oxidative Stress
Bonomini, F., Rodella, L. F., & Rezzani, R. (2015) · Aging and Disease · doi:10.14336/ad.2014.0305 · Cited by 599 · see citing works
Relationship between glycated haemoglobin levels and mean glucose levels over time
Nathan, D. M., Turgeon, H., & Regan, S. (2007) · Diabetologia · doi:10.1007/s00125-007-0803-0 · Cited by 517 · see citing works
The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading
Beck, R. W., Connor, C. G., Mullen, D. M., Wesley, D. M., & Bergenstal, R. M. (2017) · Diabetes Care · doi:10.2337/dc17-0636 · Cited by 477 · see citing works
The relationship of hemoglobin A1C to time-in-range in patients with diabetes
Vigersky, R. A., & McMahon, C. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0310 · Cited by 464 · see citing works
A new look at screening and diagnosing diabetes mellitus
Saudek, C. D., Herman, W. H., Sacks, D. B., Bergenstal, R. M., Edelman, D., & Davidson, M. B. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2007-2174 · Cited by 432 · see citing works
Short-term variability in measures of glycemia and implications for the classification of diabetes
Selvin, E. (2007) · Archives of Internal Medicine · doi:10.1001/archinte.167.14.1545 · Cited by 402 · see citing works
Assessing Glycemia in Diabetes Using Self-monitoring Blood Glucose and Hemoglobin A <sub>1c</sub>
Saudek, C. D., Derr, R. L., & Kalyani, R. R. (2006) · JAMA · doi:10.1001/jama.295.14.1688 · Cited by 373 · see citing works
Postprandial Glucose Regulation and Diabetic Complications
Ceriello, A. (2004) · Archives of Internal Medicine · doi:10.1001/archinte.164.19.2090 · Cited by 362 · see citing works
Clinical impact of glycated albumin as another glycemic control marker
Koga, M., & Kasayama, S. (2010) · Endocrine Journal · doi:10.1507/endocrj.k10e-138 · Cited by 290 · see citing works
Brown, S. A., Forlenza, G. P., Bode, B. W., Pinsker, J. E., Levy, C. J., Criego, A. B., Hansen, D. W., Hirsch, I. B., Carlson, A. L., Bergenstal, R. M., et al. (2021) · Diabetes Care · doi:10.2337/dc21-0172 · Cited by 286 · see citing works
Screening for Diabetes and Pre-Diabetes With Proposed A1C-Based Diagnostic Criteria
Olson, D. E., Rhee, M. K., Herrick, K., Ziemer, D. C., Twombly, J. G., & Phillips, L. S. (2010) · Diabetes Care · doi:10.2337/dc10-0433 · Cited by 234 · see citing works
Kennedy, L., Herman, W. H., Strange, P., Harris, A., & for the GOAL A1C Team (2006) · Diabetes Care · doi:10.2337/diacare.29.01.06.dc05-1058 · Cited by 189 · see citing works
Mobile phone text messaging in the management of diabetes
Ferrer-Roca, O., Cárdenas, A., Diaz-Cardama, A., & Pulido, P. (2004) · Journal of Telemedicine and Telecare · doi:10.1258/1357633042026341 · Cited by 171 · see citing works
Reference intervals for hemoglobin A1c in pregnant women: data from an Italian multicenter study
Mosca, A., Paleari, R., Dalfrà, M. G., Di Cianni, G., Cuccuru, I., Pellegrini, G., Malloggi, L., Bonomo, M., Granata, S., Ceriotti, F., et al. (2006) · Clinical Chemistry · doi:10.1373/clinchem.2005.064899 · Cited by 161 · see citing works
Use of HbA1c in Predicting Progression to Diabetes in French Men and Women
Droumaguet, C., Balkau, B., Simon, D., Caces, E., Tichet, J., Charles, M. A., Eschwege, E., & the DESIR Study Group (2006) · Diabetes Care · doi:10.2337/dc05-2525 · Cited by 159 · see citing works
Diabetes, Fasting Glucose Levels, and Risk of Ischemic Stroke and Vascular Events
Boden-Albala, B., Cammack, S., Chong, J., Wang, C., Wright, C., Rundek, T., Elkind, M. S. V., Paik, M. C., & Sacco, R. L. (2008) · Diabetes Care · doi:10.2337/dc07-0797 · Cited by 132 · see citing works
A critical review of mathematical models and data used in diabetology
Boutayeb, A., & Chetouani, A. (2006) · BioMedical Engineering OnLine · doi:10.1186/1475-925x-5-43 · Cited by 126 · see citing works
Relationship of A1C to Glucose Concentrations in Children With Type 1 Diabetes
Diabetes Research in Children Network (DirecNet) Study Group (2008) · Diabetes Care · doi:10.2337/dc07-1835 · Cited by 115 · see citing works
Ahn, C. H., Min, S. H., Lee, D.-H., Oh, T. J., Kim, K. M., Moon, J. H., Choi, S. H., Park, K. S., Jang, H. C., Ha, J., et al. (2017) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2017-00191 · Cited by 91 · see citing works
Monnier, L., Colette, C., & Owens, D. R. (2009) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.962 · Cited by 89 · see citing works
Osei, K., Rhinesmith, S., Gaillard, T., & Schuster, D. (2003) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2003-030686 · Cited by 86 · see citing works
Monnier, L., & Colette, C. (2009) · Diabetes Care · doi:10.2337/dc09-s310 · Cited by 82 · see citing works
Translating HbA1c measurements into estimated average glucose values in pregnant women with diabetes
Law, G. R., Gilthorpe, M. S., Secher, A. L., Temple, R., Bilous, R., Mathiesen, E. R., Murphy, H. R., & Scott, E. M. (2017) · Diabetologia · doi:10.1007/s00125-017-4205-7 · Cited by 77 · see citing works
Monnier, L., Benichou, M., Charra-Ebrard, S., Boegner, C., & Colette, C. (2005) · Diabetes & Metabolism · doi:10.1016/s1262-3636(07)70174-x · Cited by 69 · see citing works
Randløv, J., & Poulsen, J. U. (2008) · Journal of Diabetes Science and Technology · doi:10.1177/193229680800200209 · Cited by 61 · see citing works
Fangel, M. V., Nielsen, P. B., Kristensen, J. K., Larsen, T. B., Overvad, T. F., Lip, G. Y. H., & Jensen, M. B. (2019) · Circulation: Arrhythmia and Electrophysiology · doi:10.1161/circep.118.007030 · Cited by 49 · see citing works
The Diabetes Research In Children, N. (2003) · Diabetes Technology & Therapeutics · doi:10.1089/152091503322640971 · Cited by 44 · see citing works
A Novel Testing Model for Opportunistic Screening of Pre-Diabetes and Diabetes among U.S. Adults
Zhang, Y., Hu, G., Zhang, L., Mayo, R., & Chen, L. (2015) · PLOS ONE · doi:10.1371/journal.pone.0120382 · Cited by 41 · see citing works
“The optimal cutoff values for HbA1c has been intensively reported in previous studies and discussed in several review papers [4,14,15,38,41,42,43,44,45].”
BackgroundOsborn, C. Y., van Ginkel, J. R., Marrero, D. G., Rodbard, D., Huddleston, B., & Dachis, J. (2017) · JMIR mHealth and uHealth · doi:10.2196/mhealth.8781 · Cited by 33 · see citing works
US Trends in Glycemic Control, Treatment, and Comorbidity Burden in Patients With Diabetes
Shaya, F. T., Yan, X., Lin, P., Simoni‐Wastila, L., Bron, M., Baran, R., & Donner, T. W. (2010) · The Journal of Clinical Hypertension · doi:10.1111/j.1751-7176.2010.00365.x · Cited by 29 · see citing works
Murata, G. H., Hoffman, R. M., Wendel, C. S., Shah, J. H., & Duckworth, W. C. (2004) · The American Journal of the Medical Sciences · doi:10.1097/00000441-200406000-00004 · Cited by 27 · see citing works
Checkpoint inhibitor treatment induces an increase in HbA1c in nondiabetic patients
Gauci, M.-L., Boudou, P., Squara, P.-A., Delyon, J., Allayous, C., Mourah, S., Resche-Rigon, M., Lebbé, C., Baroudjian, B., & Gautier, J.-F. (2019) · Melanoma Research · doi:10.1097/cmr.0000000000000585 · Cited by 10 · see citing works
Standards of Medical Care in Diabetes
American Diabetes Association (2005) · Diabetes Care · doi:10.2337/diacare.28.suppl_1.s4 · Cited by 2 · see citing works
- Authors
- Rohlfing, C. L., Wiedmeyer, H.-M., Little, R. R., England, J. D., Tennill, A., & Goldstein, D. E.
- Affiliations
- University of Missouri (US)
- ORCID
- Little, Randie R.
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2002-02-01
- Volume
- 25
- Issue
- 2
- Pages
- 275-278
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W2110590807
- Cited by
- 987
- References
- 19
- Citations by year
- 2026: 11 · 2025: 19 · 2024: 32 · 2023: 33 · 2022: 24 · 2021: 27 · 2020: 33 · 2019: 30 · 2018: 45 · 2017: 32 · 2016: 33 · 2015: 41 · 2014: 60 · 2013: 58 · 2012: 45
- FWCI
- 18.45
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Diabetes Care (publishedVersion)
- PubMed (publishedVersion)
- Funders
- George Washington University
- Max-Planck-Gesellschaft
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- HbA1c, plasma glucose, type 1 diabetes, glycemic control, capillary blood glucose, glycemic targets, Diabetes Control and Complications Trial
- MeSH terms
- Blood Glucose, Diabetes Mellitus, Type 1, Glycated Hemoglobin, Humans, Linear Models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review