The DOI matches its Crossref record; 27 of the 29 references it cites were found in a registry or an index.
Validation of Time in Range as an Outcome Measure for Diabetes Clinical Trials
Open accessAbstract
OBJECTIVE: This study evaluated the association of time in range (TIR) of 70–180 mg/dL (3.9–10 mmol/L) with the development or progression of retinopathy and development of microalbuminuria using the Diabetes Control and Complications Trial (DCCT) data set in order to validate the use of TIR as an outcome measure for clinical trials. RESEARCH DESIGN AND METHODS: In the DCCT, blood glucose concentrations were measured at a central laboratory from seven fingerstick samples (seven-point testing: pre- and 90-min postmeals and at bedtime) collected during 1 day every 3 months. Retinopathy progression was assessed every 6 months and urinary microalbuminuria development every 12 months. Proportional hazards models were used to assess the association of TIR and other glycemic metrics, computed from the seven-point fingerstick data, with the rate of development of microvascular complications. RESULTS: Mean TIR of seven-point profiles for the 1,440 participants was 41 ± 16%. The hazard rate of development of retinopathy progression was increased by 64% (95% CI 51–78), and development of the microalbuminuria outcome was increased by 40% (95% CI 25–56), for each 10 percentage points lower TIR (P < 0.001 for each). Results were similar for mean glucose and hyperglycemia metrics. CONCLUSIONS: Based on these results, a compelling case can be made that TIR is strongly associated with the risk of microvascular complications and should be an acceptable end point for clinical trials. Although hemoglobin A1c remains a valuable outcome metric in clinical trials, TIR and other glycemic metrics—especially when measured with continuous glucose monitoring—add value as outcome measures in many studies.
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“In particular, glucose time in range (70 -180 mg/dl [3.9 -10.0 mmol/l]) and time in hypoglycemia ( < 70 mg/dl [3.9 mmol/l] and < 54 mg/dl [3.0 mmol/l]) have been used as outcomes for clinical trials 259,260 and have been endorsed as appropriate metrics for clinical care. 229”
From KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease (2022) · cites this paper as [259]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Although the evidence of HbA 1c reduction remains the most robust measure associated with chronic diabetes complications and is the only measure that is prospectively validated, more recent studies have begun to examine the relationship between time that glucose is within the target range and long-term complications and have provided the basis for glycemic targets with newer glucose monitoring”
From The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) (2021) · cites this paper as [45]
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“GMI is calculated based on the average sensor glucose over the last 14 days and provides an approximation of a laboratory-measured HbA 1c in some individuals, but it may be higher or lower than actual HbA 1c in others (45).”
From The management of type 1 diabetes in adults. A consensus report by the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) (2021) · cites this paper as [45]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“TIR is associated with microvascular complications (45,46), and a TIR of 70% roughly corresponds to an HbA 1c of 53 mmol/mol (7.0%).”
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In the citing paper
“Most recently, the beneficial effects of new medications, such as sodium glucose cotransporter-2 (SGLT-2) agents have helped individuals with type 1 diabetes increase TIR (49-51).”
From Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range (2019) · cites this paper as [50]
Experimental — accuracy not yet measured
In the citing paper
“TIR has been found to be strongly associated with the development or progression of diabetic retinopathy and microalbuminuria in type 1 and type 2 DM.16 17”
From Glucose time in range and peripheral neuropathy in type 2 diabetes mellitus and chronic kidney disease (2020) · cites this paper as [16]
In the citing paper
“In a post hoc analysis from the Diabetes Control and Complications Trial (DCCT), Beck et al. (8) calculated TIR with seven-point fingerstick glucose values and demonstrated significant associations of TIR with the development of diabetic retinopathy and microalbuminuria.”
From Time in Range in Relation to All-Cause and Cardiovascular Mortality in Patients With Type 2 Diabetes: A Prospective Cohort Study (2021) · cites this paper as [8]
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Citations
Cites
(1993) · New England Journal of Medicine · doi:10.1056/nejm199309303291401 · Cited by 24,667
International consensus on use of continuous glucose monitoring
Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., Garg, S., Heinemann, L., Hirsch, I., Amiel, S. A., et al. (2017) · Diabetes Care · doi:10.2337/dc17-1600 · Cited by 2,069
Self-citationSeaquist, E. R., Anderson, J., Childs, B., Cryer, P., Dagogo-Jack, S., Fish, L., Heller, S. R., Rodriguez, H., Rosenzweig, J., & Vigersky, R. (2013) · Diabetes Care · doi:10.2337/dc12-2480 · Cited by 1,389
International Hypoglycaemia Study Group (2017) · Diabetes Care · doi:10.2337/dc16-2215 · Cited by 608
The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading
Beck, R. W., Connor, C. G., Mullen, D. M., Wesley, D. M., & Bergenstal, R. M. (2017) · Diabetes Care · doi:10.2337/dc17-0636 · Cited by 477
Self-citationThe DCCT Research Group (1986) · Diabetes · doi:10.2337/diabetes.35.5.530 · Cited by 466
Agiostratidou, G., Anhalt, H., Ball, D., Blonde, L., Gourgari, E., Harriman, K. N., Kowalski, A. J., Madden, P., McAuliffe-Fogarty, A. H., McElwee-Malloy, M., et al. (2017) · Diabetes Care · doi:10.2337/dc17-1624 · Cited by 397
The Effect of Glucose Variability on the Risk of Microvascular Complications in Type 1 Diabetes
Kilpatrick, E. S., Rigby, A. S., & Atkin, S. L. (2006) · Diabetes Care · doi:10.2337/dc06-0293 · Cited by 376
The International Hypoglycaemia Study Group (2016) · Diabetologia · doi:10.1007/s00125-016-4146-6 · Cited by 367
The impact of non-severe hypoglycemic events on work productivity and diabetes management
Brod, M., Christensen, T., Thomsen, T. L., & Bushnell, D. M. (2011) · Value in Health · doi:10.1016/j.jval.2011.02.001 · Cited by 284
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2 of the 29 references couldn’t be matched to a known paper.
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Battelino, T., Danne, T., Bergenstal, R. M., Amiel, S. A., Beck, R., Biester, T., Bosi, E., Buckingham, B. A., Cefalu, W. T., Close, K. L., et al. (2019) · Diabetes Care · doi:10.2337/dci19-0028 · Cited by 4,237
“0 mmol/L]) with diabetes complications (49,50) as well as a relationship between TIR and A1C (26,27).”
BackgroundMethodSelf-citationKDIGO 2020 Clinical practice guideline for diabetes management in chronic kidney disease
de Boer, I. H., Caramori, M. L., Chan, J. C. N., Heerspink, H. J. L., Hurst, C., Khunti, K., Liew, A., Michos, E. D., Navaneethan, S. D., Olowu, W. A., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.06.019 · Cited by 1,399
KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease
Rossing, P., Caramori, M. L., Chan, J. C. N., Heerspink, H. J. L., Hurst, C., Khunti, K., Liew, A., Michos, E. D., Navaneethan, S. D., Olowu, W. A., et al. (2022) · Kidney International · doi:10.1016/j.kint.2022.06.008 · Cited by 1,373
Continuous glucose monitoring and metrics for clinical trials: an international consensus statement
Battelino, T., Alexander, C. M., Amiel, S. A., Arreaza-Rubin, G., Beck, R. W., Bergenstal, R. M., Buckingham, B. A., Carroll, J., Ceriello, A., Chow, E., et al. (2023) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(22)00319-9 · Cited by 831
Self-citationHolt, R. I. G., DeVries, J. H., Hess-Fischl, A., Hirsch, I. B., Kirkman, M. S., Klupa, T., Ludwig, B., Nørgaard, K., Pettus, J., Renard, E., et al. (2021) · Diabetes Care · doi:10.2337/dci21-0043 · Cited by 699
Metadata
- Authors
- Beck, R. W., Bergenstal, R. M., Riddlesworth, T. D., Kollman, C., Li, Z., Brown, A. S., & Close, K. L.
- Affiliations
- Jaeb Center for Health Research (US)
- Park Nicollet Health Services (US)
- Close Concerns (United States) (US)
- The diaTribe Foundation, San Francisco, CA
- Corresponding author
- Beck, Roy W.
- ORCID
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2018-10-23
- Volume
- 42
- Issue
- 3
- Pages
- 400-405
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- PMC
- PMC6905478
- OpenAlex
- W2897457722
- Cited by
- 793
- References
- 29
- Citations by year
- 2026: 73 · 2025: 93 · 2024: 87 · 2023: 106 · 2022: 138 · 2021: 134 · 2020: 103 · 2019: 54 · 2018: 2
- FWCI
- 57.92
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Care (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Jaeb Center for Health Research Foundation
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- time in range, glycemic control, retinopathy progression, microalbuminuria, microvascular complications, outcome measure validation, Diabetes Control and Complications Trial, continuous glucose monitoring, HbA1c, glycemic metrics
- MeSH terms
- Adult, Blood Glucose, Clinical Trials as Topic, Diabetes Mellitus, Female, Glycated Hemoglobin, Humans, Longitudinal Studies, Male, Middle Aged, Patient Care Planning, Prognosis, Research Design, Time Factors, Blood Glucose Self-Monitoring, Treatment Outcome, Outcome Assessment, Health Care, Disease Progression, Diabetes Complications
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