Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems.

Eichenlaub, Manuel; Pleus, Stefan; Rothenbühler, Martina; Bailey, Timothy S; Bally, Lia; Brazg, Ron L; Bruttomesso, Daniela; Diem, Peter; Eriksson Boija, Elisabet; Fokkert, Marion; Haug, Cornelia; Hinzmann, Rolf; Jendle, Johan; Klonoff, David C; Mader, Julia K; Makris, Konstantinos; Moser, Othmar; Nichols, James; Norgaard, Kirsten; Pemberton, John; ... (2024). Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems. Diabetes technology & therapeutics, 26(4), pp. 263-275. Mary Ann Liebert 10.1089/dia.2023.0465

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Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC), that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels is suggested that enables the collection of comparator data with these characteristics. This work is an important step towards establishing a future standard for the performance evaluation of CGM systems.

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