{"title":"Time in Range and Incident Diabetic Retinopathy: Clinical and Economic Evidence from Real-World Type 1 Diabetes Care.","authors":"Nai-Chia Chen, Viral N Shah, Robert Brett McQueen","doi":"10.1210/clinem/dgaf544","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Continuous glucose monitoring (CGM) metrics are increasingly used to study the relationship between glycemic control and diabetic complications; however, the correlated glucose measurements and unequal follow-up times in real-world CGM data necessitate more advanced analytical approaches to yield unbiased estimates. This retrospective case-cohort study aimed to estimate longitudinal changes in time in range (TIR) on progression to diabetic retinopathy among patients with type 1 diabetes (T1D).</p><p><strong>Methods: </strong>This was a retrospective case-cohort study among patients with T1D, using CGM devices. We analyzed linked CGM and electronic health record data from 161 patients with T1D, with long-term follow-up for incident diabetic retinopathy diagnoses. TIR was defined as time spent in sensor glucose between 70-180 mg/dL. Multilevel mixed-effects parametric survival models and Markov models were constructed to obtain effects of TIR (e.g., hazard ratios) and lifetime trajectories of developing retinopathy and blindness, respectively.</p><p><strong>Results: </strong>A retrospective case-cohort of 161 patients with T1D (mean duration 13.7 years) included 71 cases (baseline HbA1c 8.2%) and 90 controls (baseline HbA1c 7.3%). A 10% increase in TIR was associated with a modestly lower risk of retinopathy progression (HR 0.88; 95% CI, 0.78-0.98) and an estimated prevention of 39 cases of blindness per 1,000 individuals over time (TIR 70% vs. 40%). Economic simulation modeling suggested $2,581 lower costs per person and a gain of 0.13 quality-adjusted life years (QALYs).</p><p><strong>Conclusions: </strong>These findings can guide real-world CGM studies and support diabetes simulation models to predict future treatment outcomes from CGM metrics.</p>","PeriodicalId":520805,"journal":{"name":"The Journal of clinical endocrinology and metabolism","volume":" ","pages":""},"PeriodicalIF":5.1000,"publicationDate":"2025-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of clinical endocrinology and metabolism","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1210/clinem/dgaf544","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Background: Continuous glucose monitoring (CGM) metrics are increasingly used to study the relationship between glycemic control and diabetic complications; however, the correlated glucose measurements and unequal follow-up times in real-world CGM data necessitate more advanced analytical approaches to yield unbiased estimates. This retrospective case-cohort study aimed to estimate longitudinal changes in time in range (TIR) on progression to diabetic retinopathy among patients with type 1 diabetes (T1D).
Methods: This was a retrospective case-cohort study among patients with T1D, using CGM devices. We analyzed linked CGM and electronic health record data from 161 patients with T1D, with long-term follow-up for incident diabetic retinopathy diagnoses. TIR was defined as time spent in sensor glucose between 70-180 mg/dL. Multilevel mixed-effects parametric survival models and Markov models were constructed to obtain effects of TIR (e.g., hazard ratios) and lifetime trajectories of developing retinopathy and blindness, respectively.
Results: A retrospective case-cohort of 161 patients with T1D (mean duration 13.7 years) included 71 cases (baseline HbA1c 8.2%) and 90 controls (baseline HbA1c 7.3%). A 10% increase in TIR was associated with a modestly lower risk of retinopathy progression (HR 0.88; 95% CI, 0.78-0.98) and an estimated prevention of 39 cases of blindness per 1,000 individuals over time (TIR 70% vs. 40%). Economic simulation modeling suggested $2,581 lower costs per person and a gain of 0.13 quality-adjusted life years (QALYs).
Conclusions: These findings can guide real-world CGM studies and support diabetes simulation models to predict future treatment outcomes from CGM metrics.