Literature DB >> 28733374

The Fallacy of Average: How Using HbA1c Alone to Assess Glycemic Control Can Be Misleading.

Roy W Beck1, Crystal G Connor2, Deborah M Mullen3, David M Wesley3,4, Richard M Bergenstal3.   

Abstract

HbA1c is a valuable metric for comparing treatment groups in a randomized trial, for assessing glycemic trends in a population over time, or for cross-sectional comparisons of glycemic control in different populations. However, what is not widely appreciated is that HbA1c may not be a good indicator of an individual patient's glycemic control because of the wide range of mean glucose concentrations and glucose profiles that can be associated with a given HbA1c level. To illustrate this point, we plotted mean glucose measured with continuous glucose monitoring (CGM) versus central laboratory-measured HbA1c in 387 participants in three randomized trials, showing that not infrequently HbA1c may underestimate or overestimate mean glucose, sometimes substantially. Thus, if HbA1c is to be used to assess glycemic control, it is imperative to know the patient's actual mean glucose to understand how well HbA1c is an indicator of the patient's glycemic control. With knowledge of the mean glucose, an estimated HbA1c (eA1C) can be calculated with the formula provided in this article to compare with the measured HbA1c. Estimating glycemic control from HbA1c alone is in essence applying a population average to an individual, which can be misleading. Thus, a patient's CGM glucose profile has considerable value for optimizing his or her diabetes management. In this era of personalized, precision medicine, there are few better examples with respect to the fallacy of applying a population average to a specific patient rather than using specific information about the patient to determine the optimal approach to treatment.
© 2017 by the American Diabetes Association.

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Year:  2017        PMID: 28733374      PMCID: PMC5521971          DOI: 10.2337/dc17-0636

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


  24 in total

1.  Hemoglobin A1C, mean glucose, and persistence of glycation ratios in insulin-treated diabetes.

Authors:  Nicholas B Argento; Katherine Nakamura; Robert D Sala; Peter Simpson
Journal:  Endocr Pract       Date:  2014-03       Impact factor: 3.443

2.  Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring.

Authors:  Roy Malka; David M Nathan; John M Higgins
Journal:  Sci Transl Med       Date:  2016-10-05       Impact factor: 17.956

3.  Continuous Glucose Monitoring Versus Usual Care in Patients With Type 2 Diabetes Receiving Multiple Daily Insulin Injections: A Randomized Trial.

Authors:  Roy W Beck; Tonya D Riddlesworth; Katrina Ruedy; Andrew Ahmann; Stacie Haller; Davida Kruger; Janet B McGill; William Polonsky; David Price; Stephen Aronoff; Ronnie Aronson; Elena Toschi; Craig Kollman; Richard Bergenstal
Journal:  Ann Intern Med       Date:  2017-08-22       Impact factor: 25.391

4.  Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial.

Authors:  Roy W Beck; Tonya Riddlesworth; Katrina Ruedy; Andrew Ahmann; Richard Bergenstal; Stacie Haller; Craig Kollman; Davida Kruger; Janet B McGill; William Polonsky; Elena Toschi; Howard Wolpert; David Price
Journal:  JAMA       Date:  2017-01-24       Impact factor: 56.272

5.  High and low hemoglobin glycation phenotypes in type 1 diabetes: a challenge for interpretation of glycemic control.

Authors:  James M Hempe; Ricardo Gomez; Robert J McCarter; Stuart A Chalew
Journal:  J Diabetes Complications       Date:  2002 Sep-Oct       Impact factor: 2.852

6.  Unexplained variability of glycated haemoglobin in non-diabetic subjects not related to glycaemia.

Authors:  J S Yudkin; R D Forrest; C A Jackson; A J Ryle; S Davie; B J Gould
Journal:  Diabetologia       Date:  1990-04       Impact factor: 10.122

7.  Relationship of A1C to glucose concentrations in children with type 1 diabetes: assessments by high-frequency glucose determinations by sensors.

Authors:  Darrell M Wilson
Journal:  Diabetes Care       Date:  2007-12-04       Impact factor: 19.112

8.  Relationship of glycated haemoglobin and reported hypoglycaemia to cardiovascular outcomes in patients with type 2 diabetes and recent acute coronary syndrome events: The EXAMINE trial.

Authors:  Simon R Heller; Richard M Bergenstal; William B White; Stuart Kupfer; George L Bakris; William C Cushman; Cyrus R Mehta; Steven E Nissen; Craig A Wilson; Faiez Zannad; Yuyin Liu; Noah M Gourlie; Christopher P Cannon
Journal:  Diabetes Obes Metab       Date:  2017-02-27       Impact factor: 6.577

9.  REPLACE-BG: A Randomized Trial Comparing Continuous Glucose Monitoring With and Without Routine Blood Glucose Monitoring in Adults With Well-Controlled Type 1 Diabetes.

Authors:  Grazia Aleppo; Katrina J Ruedy; Tonya D Riddlesworth; Davida F Kruger; Anne L Peters; Irl Hirsch; Richard M Bergenstal; Elena Toschi; Andrew J Ahmann; Viral N Shah; Michael R Rickels; Bruce W Bode; Athena Philis-Tsimikas; Rodica Pop-Busui; Henry Rodriguez; Emily Eyth; Anuj Bhargava; Craig Kollman; Roy W Beck
Journal:  Diabetes Care       Date:  2017-02-16       Impact factor: 19.112

10.  Estimation of the glycation gap in diabetic patients with stable glycemic control.

Authors:  Santiago Rodríguez-Segade; Javier Rodríguez; José M García Lopez; Felipe F Casanueva; Félix Camiña
Journal:  Diabetes Care       Date:  2012-09-06       Impact factor: 19.112

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  97 in total

1.  A Review of Continuous Glucose Monitoring Data Interpretation in the Age of Automated Insulin Delivery.

Authors:  Laya Ekhlaspour; Ideen Tabatabai; Bruce Buckingham
Journal:  J Diabetes Sci Technol       Date:  2019-05-26

2.  Identification of clinically relevant dysglycemia phenotypes based on continuous glucose monitoring data from youth with type 1 diabetes and elevated hemoglobin A1c.

Authors:  Anna R Kahkoska; Linda A Adair; Allison E Aiello; Kyle S Burger; John B Buse; Jamie Crandell; David M Maahs; Crystal T Nguyen; Michael R Kosorok; Elizabeth J Mayer-Davis
Journal:  Pediatr Diabetes       Date:  2019-04-29       Impact factor: 4.866

3.  Limitations of hemoglobin A1c in the management of type 2 diabetes mellitus.

Authors:  Nemin Adam Zhu; Sonja Reichert; Stewart B Harris
Journal:  Can Fam Physician       Date:  2020-02       Impact factor: 3.275

Review 4.  Optimizing Diabetes Care With the Standardized Continuous Glucose Monitoring Report.

Authors:  Ji H Cj Chun; Megan S O'Neill
Journal:  Clin Diabetes       Date:  2020-04

Review 5.  Defining Outcomes for β-cell Replacement Therapy in the Treatment of Diabetes: A Consensus Report on the Igls Criteria From the IPITA/EPITA Opinion Leaders Workshop.

Authors:  Michael R Rickels; Peter G Stock; Eelco J P de Koning; Lorenzo Piemonti; Johann Pratschke; Rodolfo Alejandro; Melena D Bellin; Thierry Berney; Pratik Choudhary; Paul R Johnson; Raja Kandaswamy; Thomas W H Kay; Bart Keymeulen; Yogish C Kudva; Esther Latres; Robert M Langer; Roger Lehmann; Barbara Ludwig; James F Markmann; Marjana Marinac; Jon S Odorico; François Pattou; Peter A Senior; James A M Shaw; Marie-Christine Vantyghem; Steven White
Journal:  Transplantation       Date:  2018-09       Impact factor: 4.939

6.  Systematic review and meta-analysis of patient race/ethnicity, socioeconomics, and quality for adult type 2 diabetes.

Authors:  Woolton Lee; Jennifer T Lloyd; Katherine Giuriceo; Timothy Day; William Shrank; Rahul Rajkumar
Journal:  Health Serv Res       Date:  2020-07-27       Impact factor: 3.402

7.  Estimation of Hemoglobin A1c from Continuous Glucose Monitoring Data in Individuals with Type 1 Diabetes: Is Time In Range All We Need?

Authors:  Chiara Fabris; Lutz Heinemann; Roy Beck; Claudio Cobelli; Boris Kovatchev
Journal:  Diabetes Technol Ther       Date:  2020-07       Impact factor: 6.118

8.  Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials.

Authors:  Roy W Beck; Richard M Bergenstal; Tonya D Riddlesworth; Craig Kollman; Zhaomian Li; Adam S Brown; Kelly L Close
Journal:  Diabetes Care       Date:  2018-10-23       Impact factor: 19.112

9.  The Relationship Between CGM-Derived Metrics, A1C, and Risk of Hypoglycemia in Older Adults With Type 1 Diabetes.

Authors:  Elena Toschi; Christine Slyne; Kayla Sifre; Rachel O'Donnell; Jordan Greenberg; Astrid Atakov-Castillo; Sam Carl; Medha Munshi
Journal:  Diabetes Care       Date:  2020-05-27       Impact factor: 19.112

Review 10.  Defining outcomes for β-cell replacement therapy in the treatment of diabetes: a consensus report on the Igls criteria from the IPITA/EPITA opinion leaders workshop.

Authors:  Michael R Rickels; Peter G Stock; Eelco J P de Koning; Lorenzo Piemonti; Johann Pratschke; Rodolfo Alejandro; Melena D Bellin; Thierry Berney; Pratik Choudhary; Paul R Johnson; Raja Kandaswamy; Thomas W H Kay; Bart Keymeulen; Yogish C Kudva; Esther Latres; Robert M Langer; Roger Lehmann; Barbara Ludwig; James F Markmann; Marjana Marinac; Jon S Odorico; François Pattou; Peter A Senior; James A M Shaw; Marie-Christine Vantyghem; Steven White
Journal:  Transpl Int       Date:  2018-04       Impact factor: 3.782

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