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      Efficacy and safety of flash glucose monitoring in patients with type 1 and type 2 diabetes: a systematic review and meta-analysis

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          Abstract

          Introduction

          Flash glucose monitoring (FGM) is a factory-calibrated sensor-based technology for the measurement of interstitial glucose. We performed a systematic review and meta-analysis to assess its efficacy and safety in patients with type 1 and type 2 diabetes.

          Research design and methods

          PubMed, CENTRAL, Scopus and Web of Science were searched in July 2019. Twelve studies with a follow-up longer than 8 weeks, evaluating 2173 patients on prandial insulin, multiple daily insulin injections or continuous subcutaneous insulin infusion were included. The following data were extracted: HbA1c, time in range, time above 180 mg/dL, time below 70 mg/dL, frequency of hypoglycemic events, number of self-monitoring of blood glucose (SMBG) measurements, total daily insulin dose, patient-reported outcomes, adverse events, and discontinuation rate. A comparison with SMBG was conducted.

          Results

          FGM use was associated with a reduction in HbA1c (−0.26% (−3 mmol/mol); p=0.002) from baseline to the last available follow-up, which correlated with HbA1c levels at baseline (−0.4% (−4 mmol/mol) for each 1.0% (11 mmol/mol) of HbA1c above 7.2% (55 mmol/mol)). Also, a decrease in time below 70 mg/dL was found (−0.60 hours/day; p=0.04). Favorable findings in patient-reported outcomes and no device-related serious adverse events were reported. When compared with SMBG, FGM was characterized by no statistically different change in HbA1c (p=0.09), with lower number of SMBG measurements per day (−3.76 n/day; p<0.001) and risk of discontinuation (relative risk=0.42; p=0.001). A limited number of studies, with a heterogeneous design and usually with a short-term follow-up and without specific training, were found.

          Conclusions

          The present review provides evidence for the use of FGM as an effective strategy for the management of diabetes.

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          Most cited references33

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          Flash Glucose-Sensing Technology as a Replacement for Blood Glucose Monitoring for the Management of Insulin-Treated Type 2 Diabetes: a Multicenter, Open-Label Randomized Controlled Trial

          Introduction Glycemic control in participants with insulin-treated diabetes remains challenging. We assessed safety and efficacy of new flash glucose-sensing technology to replace self-monitoring of blood glucose (SMBG). Methods This open-label randomized controlled study (ClinicalTrials.gov, NCT02082184) enrolled adults with type 2 diabetes on intensive insulin therapy from 26 European diabetes centers. Following 2 weeks of blinded sensor wear, 2:1 (intervention/control) randomization (centrally, using biased-coin minimization dependant on study center and insulin administration) was to control (SMBG) or intervention (glucose-sensing technology). Participants and investigators were not masked to group allocation. Primary outcome was difference in HbA1c at 6 months in the full analysis set. Prespecified secondary outcomes included time in hypoglycemia, effect of age, and patient satisfaction. Results Participants (n = 224) were randomized (149 intervention, 75 controls). At 6 months, there was no difference in the change in HbA1c between intervention and controls: −3.1 ± 0.75 mmol/mol, [−0.29 ± 0.07% (mean ± SE)] and −3.4 ± 1.04 mmol/mol (−0.31 ± 0.09%) respectively; p = 0.8222. A difference was detected in participants aged <65 years [−5.7 ± 0.96 mmol/mol (−0.53 ± 0.09%) and −2.2 ± 1.31 mmol/mol (−0.20 ± 0.12%), respectively; p = 0.0301]. Time in hypoglycemia <3.9 mmol/L (70 mg/dL) reduced by 0.47 ± 0.13 h/day [mean ± SE (p = 0.0006)], and <3.1 mmol/L (55 mg/dL) reduced by 0.22 ± 0.07 h/day (p = 0.0014) for intervention participants compared with controls; reductions of 43% and 53%, respectively. SMBG frequency, similar at baseline, decreased in intervention participants from 3.8 ± 1.4 tests/day (mean ± SD) to 0.3 ± 0.7, remaining unchanged in controls. Treatment satisfaction was higher in intervention compared with controls (DTSQ 13.1 ± 0.50 (mean ± SE) and 9.0 ± 0.72, respectively; p < 0.0001). No serious adverse events or severe hypoglycemic events were reported related to sensor data use. Forty-two serious events [16 (10.7%) intervention participants, 12 (16.0%) controls] were not device-related. Six intervention participants reported nine adverse events for sensor-wear reactions (two severe, six moderate, one mild). Conclusion Flash glucose-sensing technology use in type 2 diabetes with intensive insulin therapy results in no difference in HbA1c change and reduced hypoglycemia, thus offering a safe, effective replacement for SMBG. Trial registration ClinicalTrials.gov identifier: NCT02082184. Funding Abbott Diabetes Care. Electronic supplementary material The online version of this article (doi:10.1007/s13300-016-0223-6) contains supplementary material, which is available to authorized users.
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            Real-world flash glucose monitoring patterns and associations between self-monitoring frequency and glycaemic measures: A European analysis of over 60 million glucose tests

            Randomised controlled trials demonstrate that using flash glucose monitoring improves glycaemic control but it is unclear whether this applies outside trial conditions. We investigated glucose testing patterns in users worldwide under real life settings to establish testing frequency and association with glycaemic parameters.
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              Relationship of baseline HbA1c and efficacy of current glucose-lowering therapies: a meta-analysis of randomized clinical trials.

              Baseline glycated haemoglobin (HbA(1c)) concentrations vary between clinical trials of glucose-lowering agents and this may affect interpretation of clinical efficacy. The objective of this study is to quantify the relationship between baseline HbA(1c) and reduction of HbA(1c) in clinical trials. PubMed literature searches from 1991 to 2007. Randomized controlled studies with placebo-controlled or comparator arms [> or = 9 patients in the intent-to-treat (ITT) population] ranging in duration from 23 to 52 weeks, in which baseline and change in glycated haemoglobin (HbA(1c)) were reported. The relationship between baseline HbA(1c) and change in HbA(1c) was analysed by a weighted least-squared regression model accounting for ITT population and variance of HbA(1c) change. Fourteen per cent of independently abstracted studies met the selection criteria. Meta-analysis from 59 clinical trials (8479 patients) produced weighted R(2) of 0.35 (P < 0.0001) for the association of baseline HbA(1c) and absolute change in HbA(1c). Subanalysis of eight metformin clinical trials demonstrated a stronger association [weighted R(2) of 0.67 (P = 0.0130)]. Exclusion of metformin clinical trials from the overall meta-analysis (n = 51) yielded a weighted R(2) of 0.31 (P < 0.0001). Subanalyses of clinical trials of glucose-lowering therapies predominantly targeting fasting (n = 37) or postprandial (n = 22) blood glucose produced weighted R(2) values of 0.27 (P < 0.001) and 0.42 (P < 0.005), respectively. These data demonstrate a positive relationship between baseline HbA(1c) and the magnitude of HbA(1c) change across 10 categories of glucose-lowering therapies, irrespective of class or mode of action. These observations should be considered when assessing clinical efficacy of diabetes therapies derived from clinical trials.
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                Author and article information

                Journal
                BMJ Open Diabetes Res Care
                BMJ Open Diabetes Res Care
                bmjdrc
                bmjdrc
                BMJ Open Diabetes Research & Care
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2052-4897
                2020
                1 June 2020
                : 8
                : 1
                : e001092
                Affiliations
                [1]departmentDepartment of Emergency and Organ Transplantation , University of Bari , Bari, Puglia, Italy
                Author notes
                [Correspondence to ] Dr Francesco Giorgino; francesco.giorgino@ 123456uniba.it
                Author information
                http://orcid.org/0000-0002-1175-8998
                http://orcid.org/0000-0002-2728-7721
                http://orcid.org/0000-0001-7372-2678
                Article
                bmjdrc-2019-001092
                10.1136/bmjdrc-2019-001092
                7265013
                32487593
                9f4b31c6-ac1e-4d03-9e29-93879811dcc0
                © Author(s) (or their employer(s)) 2020. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 02 December 2019
                : 01 May 2020
                : 08 May 2020
                Categories
                Emerging Technologies, Pharmacology and Therapeutics
                1506
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                insulin therapy,glucose monitoring,glucose monitoring technologies,blood glucose self-monitoring

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