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REPLACE-BG: A Randomized Trial Comparing Continuous Glucose Monitoring With and Without Routine Blood Glucose Monitoring in Adults With Well-Controlled Type 1 Diabetes
Open accessAbstract
OBJECTIVE: To determine whether the use of continuous glucose monitoring (CGM) without confirmatory blood glucose monitoring (BGM) measurements is as safe and effective as using CGM adjunctive to BGM in adults with well-controlled type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: A randomized noninferiority clinical trial was conducted at 14 sites in the T1D Exchange Clinic Network. Participants were ≥18 years of age (mean 44 ± 14 years), had T1D for ≥1 year (mean duration 24 ± 12 years), used an insulin pump, and had an HbA1c ≤9.0% (≤75 mmol/mL) (mean 7.0 ± 0.7% [53 ± 7.7 mmol/mol]); prestudy, 47% were CGM users. Participants were randomly assigned 2:1 to the CGM-only (n = 149) or CGM+BGM (n = 77) group. The primary outcome was time in range (70–180 mg/dL) over the 26-week trial, with a prespecified noninferiority limit of 7.5%. RESULTS: CGM use averaged 6.7 ± 0.5 and 6.8 ± 0.4 days/week in the CGM-only and CGM+BGM groups, respectively, over the 26-week trial. BGM tests per day (including the two required daily for CGM calibration) averaged 2.8 ± 0.9 and 5.4 ± 1.4 in the two groups, respectively (P < 0.001). Mean time in 70–180 mg/dL was 63 ± 13% at both baseline and 26 weeks in the CGM-only group and 65 ± 13% and 65 ± 11% in the CGM+BGM group (adjusted difference 0%; one-sided 95% CI −2%). No severe hypoglycemic events occurred in the CGM-only group, and one occurred in the CGM+BGM group. CONCLUSIONS: Use of CGM without regular use of confirmatory BGM is as safe and effective as using CGM with BGM in adults with well-controlled T1D at low risk for severe hypoglycemia.
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“Numerous studies have demonstrated significant clinical benefits of CGM use in people with diabetes regardless of insulin delivery method (1-15).”
From Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range (2019) · cites this paper as [2]
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“However, the increasing accuracy of the devices and at least one RCT comparing nonadjunctive to adjunctive use (191) has led the FDA to approve most current CGM devices for nonadjunctive use in the U.S.”
From Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus (2023) · cites this paper as [191]
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“Based on the results of multiple studies reporting a strong linear relationship between percent time in range (TIR) (70–180 mg/dL) and A1C in persons with T1D and T2D”
From American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update. (2022) · cites this paper as [154]
Experimental — accuracy not yet measuredIn the citing paper
“CGM systems are generally nonadjunctive, meaning they do not require BGM confirmation for treatment decisions like insulin dosing or treating hypoglycemia, except in certain clinical situations (see BLOOD GLUCOSE MONITORING, above) (44-46).”
From 7. Diabetes Technology: Standards of Care in Diabetes—2025 (2025) · cites this paper as [44]
In the citing paper
“Some of these non-iCGM-approved CGM devices require additional user verification of blood glucose levels to be performed for making treatment decisions, termed adjunctive.”
From Importance of FDA-integrated continuous glucose monitors to ensure accuracy of continuous glucose monitoring (2025) · cites this paper as [12]
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Karakus, K. E., Akturk, H. K., Alonso, G. T., Snell-Bergeon, J. K., & Shah, V. N. (2023) · Diabetes Care · doi:10.2337/dc23-0495 · Cited by 52
Self-citationTechnology Integration: The Role of the Diabetes Care and Education Specialist in Practice
Isaacs, D. M., Cox, C. E., Schwab, K., Oser, T. K., RINKER, J. K., Mason, M. J., Greenwood, D. A., & Albanese-O’Neill, A. (2020) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721720935123 · Cited by 54
Monitoring of Pediatric Type 1 Diabetes
Marks, B. E., & Wolfsdorf, J. I. (2020) · Frontiers in Endocrinology · doi:10.3389/fendo.2020.00128 · Cited by 55
Eichenlaub, M., Pleus, S., Rothenbühler, M., Bailey, T. S., Bally, L., Brazg, R., Bruttomesso, D., Diem, P., Boija, E. E., Fokkert, M. J., et al. (2024) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0465 · Cited by 51
The History, Evolution and Future of Continuous Glucose Monitoring (CGM)
Bender, C., Vestergaard, P., & Cichosz, S. L. (2025) · Diabetology · doi:10.3390/diabetology6030017 · Cited by 43
Aleppo, G., & Webb, K. M. (2018) · Endocrine Practice · doi:10.4158/ep-2018-0097 · Cited by 45
Self-citationRodbard, D. (2022) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14906 · Cited by 45
Diabetes Technology Use in Adults with Type 1 and Type 2 Diabetes
Kravarusic, J., & Aleppo, G. (2019) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2019.10.006 · Cited by 46
Self-citationHerrero, P., Alalitei, A., Reddy, M., Georgiou, P., & Oliver, N. S. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0387 · Cited by 44
Continuous Glucose Monitoring for Prediabetes: What Are the Best Metrics?
Zahalka, S. J., Galindo, R. J., Shah, V. N., & Wang, C. C. L. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968241242487 · Cited by 53
Self-citationCichosz, S. L., Jensen, M. H., & Olesen, S. S. (2024) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0532 · Cited by 42
Role of continuous glucose monitoring in the management of glycogen storage disorders
Herbert, M., Pendyal, S., Rairikar, M. V., Halaby, C. A., Benjamin, R. W., & Kishnani, P. S. (2018) · Journal of Inherited Metabolic Disease · doi:10.1007/s10545-018-0200-5 · Cited by 42
“Trials in diabetic populations have shown its utility in improving glycemic control, as evidenced by reduction in glycosylated hemoglobin (HbA1c) and preventing hypo- and hyperglycemic episodes (Beck et al 2017; Spaic et al 2017; Lind et al 2017; Aleppo et al 2017).”
BackgroundPeeks, F., Hoogeveen, I. J., Feldbrugge, R. L., Burghard, R., de Boer, F., Fokkert‐Wilts, M. J., van der Klauw, M. M., Oosterveer, M. H., & Derks, T. G. J. (2021) · Journal of Inherited Metabolic Disease · doi:10.1002/jimd.12383 · Cited by 42
Montaser, E., Fabris, C., & Kovatchev, B. P. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0104 · Cited by 44
Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases
ALMURASHI, A. M., Rodriguez, E., & Garg, S. K. (2023) · Journal of the Indian Institute of Science · doi:10.1007/s41745-022-00348-3 · Cited by 55
Cichosz, S. L., Jensen, M. H., & Hejlesen, O. K. (2021) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2021.104472 · Cited by 42
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Choudhary, P., Bellido, V., Graner, M., Altpeter, B., Cicchetti, A., Durand‐Zaleski, I., & Kristensen, F. B. (2021) · Diabetes Therapy · doi:10.1007/s13300-021-01132-9 · Cited by 43
Prabhu Navis, J., Leelarathna, L., Mubita, W., Urwin, A., Rutter, M. K., Schofield, J., & Thabit, H. (2021) · Acta Diabetologica · doi:10.1007/s00592-020-01614-5 · Cited by 39
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Self-citationNew and Emerging Technologies in Type 1 Diabetes
Sherwood, J. S., Russell, S. J., & Putman, M. S. (2020) · Endocrinology and Metabolism Clinics of North America · doi:10.1016/j.ecl.2020.07.006 · Cited by 46
Penalty weighted glucose prediction models could lead to better clinically usage
Cichosz, S. L., Kronborg, T., Jensen, M. H., & Hejlesen, O. K. (2021) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2021.104865 · Cited by 37
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Self-citationIdentifying the deficiencies of currently available CGM to improve uptake and benefit
Barnard‐Kelly, K. D., Martínez‐Brocca, M. A., Glatzer, T., & Oliver, N. (2024) · Diabetic Medicine · doi:10.1111/dme.15338 · Cited by 37
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“12-14 Many but not all CGM systems are nonadjunctive.”
Metadata
- Authors
- Aleppo, G., Ruedy, K. J., Riddlesworth, T. D., Kruger, D. F., Peters, A. L., Hirsch, I., Bergenstal, R. M., Toschi, E., Ahmann, A. J., Shah, V. N., Rickels, M. R., Bode, B. W., Philis-Tsimikas, A., Pop-Busui, R., Rodriguez, H., Eyth, E., Bhargava, A., Kollman, C., Beck, R. W., & for the REPLACE-BG Study Group
- Affiliations
- Northwestern University (US)
- Jaeb Center for Health Research (US)
- Henry Ford Health (US)
- University of Southern California (US)
- University of Washington (US)
- Park Nicollet Health Services (US)
- Joslin Diabetes Center (US)
- Oregon Health & Science University (US)
- Barbara Davis Center for Childhood Diabetes, Aurora, CO
- University of Pennsylvania (US)
- Atlanta Diabetes Associates (US)
- Scripps Whittier Diabetes Institute, La Jolla, CA
- University of Michigan, Ann Arbor, MI
- University of South Florida (US)
- Iowa Diabetes and Endocrinology Research Center (US)
- Corresponding author
- Riddlesworth, Tonya D.
- ORCID
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2017-02-16
- Volume
- 40
- Issue
- 4
- Pages
- 538-545
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- PMC
- PMC5864100
- OpenAlex
- W2589083807
- Semantic Scholar
- 90d778291a6be773ec0116f890b79ecf1b9a36bb
- Cited by
- 329
- References
- 25
- Citations by year
- 2026: 30 · 2025: 27 · 2024: 38 · 2023: 43 · 2022: 37 · 2021: 36 · 2020: 39 · 2019: 27 · 2018: 31 · 2017: 19
- FWCI
- 25.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Care (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- Leona M. and Harry B. Helmsley Charitable Trust
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Keywords
- continuous glucose monitoring, type 1 diabetes, blood glucose monitoring, time in range, insulin pump therapy, hypoglycemia, glycemic control, non-inferiority, adults
- MeSH terms
- Adult, Aged, Blood Glucose, Diabetes Mellitus, Type 1, Female, Glycated Hemoglobin, Humans, Insulin Infusion Systems, Male, Middle Aged, Socioeconomic Factors, Blood Glucose Self-Monitoring, Young Adult
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