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. 2024 Nov 14:19322968241296097.
doi: 10.1177/19322968241296097. Online ahead of print.

The Need for Standardization of Continuous Glucose Monitoring Performance Evaluation: An Opinion by the International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Continuous Glucose Monitoring

Stefan Pleus  1   2 , Manuel Eichenlaub  2 , Elisabet Eriksson Boija  1   3 , Marion Fokkert  1   4 , Rolf Hinzmann  1   5 , Johan Jendle  1   6 , David C Klonoff  1   7 , Konstantinos Makris  1   8 , James H Nichols  1   9 , John Pemberton  1   10 , Elizabeth Selvin  1   11 , Robbert J Slingerland  1   4 , Andreas Thomas  1   12 , Nam K Tran  1   13 , Lilian Witthauer  1   14   15 , Guido Freckmann  1   2
Affiliations

The Need for Standardization of Continuous Glucose Monitoring Performance Evaluation: An Opinion by the International Federation of Clinical Chemistry and Laboratory Medicine Working Group on Continuous Glucose Monitoring

Stefan Pleus et al. J Diabetes Sci Technol. .

Abstract

Metrics derived from continuous glucose monitoring (CGM) systems are often discordant between systems. A major cause is that CGM systems are not standardized; they use various algorithms and calibration methods, leading to discordant CGM readings across systems. This discordance can be addressed by standardizing CGM performance assessments: If manufacturers aim their CGM systems at the same target, then CGM readings will align across systems. This standardization should include the comparator device, sample origin, and study procedures. With better aligned CGM readings, CGM-derived metrics will subsequently also align better between systems.

Keywords: IFCC; continuous glucose monitoring; standardization.

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Conflict of interest statement

Declaration of Conflicting InterestsThe author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: SP and ME are employees of Institute for Diabetes Technology (Institut für Diabetes-Technologie Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm; IfDT), Ulm, Germany.EEB has no disclosures.MF received lecture fees from Menarini.RH—Independent medical & scientific consultant, former employee of Roche Diabetes Care.JJ has been a lecturer/member of the scientific advisory boards at the following companies: Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Medtronic, Nordic InfuCare, Novo Nordisk, and Sanofi.DCK is a consultant for Afon, Better Therapeutics, Integrity, Lifecare, Nevro, Novo, Samsung, and Thirdwayv. KM has nothing to disclose.JHN has received research support from Abbott.JP—Advisory panel for ROCHE Diabetes Care and Abbott; speaker fees from Insulet and Dexcom.ES is supported by grants from the US National Institutes of Health (NIH) and has received donated materials related to NIH-supported research from Abbott Diabetes Care, Roche Diagnostics, Siemens Diagnostics, Ortho Clinical Diagnostics, Abbott Diagnostics, Asahi Kasei Pharma Corp, GlycoMark Corp.RJS is chair of the Clinical Chemistry Department of Isala which carries out clinical studies, eg, with medical devices for diabetes therapy on its own initiative and on behalf of various companies. RJS has received speaker’s honoraria or consulting fees in the last 3 years from Roche and Menarini.AT is a freelance consultant. He has received fees for lectures or consultancy fees from Abbott, Berlin Chemie, Dexcom, Evivamed, Menarini, Novo Nordisk, Roche and Sanofi in the last 3 years.NKT is a consultant for Roche Diagnostics and Roche Molecular Systems, received honoraria from Nova Biomedical and Thermo Fisher, and Chair (2024-2026), Critical and Point-of-Care Testing (CPOCT) Division, Association for Diagnostics and Laboratory Medicine (ADLM).LW has nothing to disclose.GF is general manager and medical director of the IfDT, which carries out clinical studies, eg, with medical devices for diabetes therapy on its own initiative and on behalf of various companies. GF/IfDT have received speakers’ honoraria or consulting fees in the last 3 years Abbott, Berlin Chemie, Boydsense, Dexcom, Glucoset, i-SENS, Lilly, Menarini, Novo Nordisk, Perfood, Pharmasens, Roche, Sinocare, Terumo, Ypsomed.

Figures

Figure 1.
Figure 1.
(a) CGM profiles of three factory-calibrated CGM systems from different manufactures simultaneously worn by the same person over the course of a single day. The box in the top left corner provides the respective percentages for the times below range (TBR), times in range (TIR), and times above range (TAR). (b)-(d) Weighted Deming regression plots between readings from different CGM systems illustrating systematic differences in CGM readings (constant offset and/or glucose-dependent over- or underestimation): The black lines show the line of identity, and the red dashed lines display the linear regression fit.
Figure 2.
Figure 2.
Illustration of the IFCC working group on CGM’s approach to minimize discrepancies between CGM readings. Without standardization, each manufacturer uses their individual comparator procedure (target) and while readings of their own CGM system will scatter around their individual target, CGM readings from different systems are substantially discordant (panel (a)). With standardization, scattering of CGM readings around the target will not necessarily change, but readings from every CGM system will scatter around the same target and thus align better (panel (b)).
See this image and copyright information in PMC

References

    1. Battelino T, Danne T, Bergenstal RM, et al.. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care. 2019;42(8):1593-1603. doi:10.2337/dci19-0028. - DOI - PMC - PubMed
    1. Kumagai R, Muramatsu A, Fujii M, et al.. Comparison of glucose monitoring between Freestyle Libre Pro and iPro2 in patients with diabetes mellitus. J Diabetes Investig. 2019;10(3):851-856. doi:10.1111/jdi.12970. - DOI - PMC - PubMed
    1. Michalak A, Pagacz K, Młynarski W, Szadkowska A, Fendler W. Discrepancies between methods of continuous glucose monitoring in key metrics of glucose control in children with type 1 diabetes. Pediatr Diabetes. 2019;20(5):604-612. doi:10.1111/pedi.12854. - DOI - PubMed
    1. Pleus S, Kamecke U, Waldenmaier D, et al.. Time in specific glucose ranges, glucose management indicator, and glycemic variability: impact of Continuous Glucose Monitoring (CGM) system model and sensor on CGM metrics. J Diabetes Sci Technol. 2021;15(5):1104-1110. doi:10.1177/1932296820931825. - DOI - PMC - PubMed
    1. Freckmann G, Pleus S, Schauer S, et al.. Choice of continuous glucose monitoring systems may affect metrics: clinically relevant differences in times in ranges. Exp Clin Endocrinol Diabetes. 2022;130(5):343-350. doi:10.1055/a-1347-2550. - DOI - PubMed