Time in range for multiple technologies in type 1 diabetes: a systematic review and network meta-analysis

Pease, Anthony P.; Lo, Clement; Earnest, Arul; Kiriakova, Velislava; Liew, Danny; Zoungas, Sophia

doi:10.2337/figshare.12116691.v1

Cited by 8 publications

(8 citation statements)

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“…-The selection of data inputs was informed initially by systematic reviews and network meta-analyses completed as part of AP's doctoral thesis. (83,93,94) Treatment effects were derived primarily from an Australian pediatric randomized controlled trial with study authors also collaborating on the current economic evaluation. (95) Australian datasets in the public domain regarding the population with type 1 diabetes were then assessed.…”

Section: Mean (Low Inputhigh Input) Values * For the Variables In Sup...mentioning

confidence: 99%

The Cost of Control: Cost-effectiveness Analysis of Hybrid Closed-Loop Therapy in Youth

et al. 2022

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OBJECTIVE Hybrid closed-loop (HCL) therapy is an efficacious management strategy for young people with type 1 diabetes. However, high costs prevent equitable access. We thus sought to evaluate the cost-effectiveness of HCL therapy compared with current care among young people with type 1 diabetes in Australia. RESEARCH DESIGN AND METHODS A patient-level Markov model was constructed to simulate disease progression for young people with type 1 diabetes using HCL therapy versus current care, with follow-up from 12 until 25 years of age. Downstream health and economic consequences were compared via decision analysis. Treatment effects and proportions using different technologies to define “current care” were based primarily on data from an Australian pediatric randomized controlled trial. Transition probabilities and utilities for health states were sourced from published studies. Costs were considered from the Australian health care system’s perspective. An annual discount rate of 5% was applied to future costs and outcomes. Uncertainty was evaluated with probabilistic and deterministic sensitivity analyses. RESULTS Use of HCL therapy resulted in an incremental cost-effectiveness ratio of Australian dollars (AUD) $32,789 per quality-adjusted life year (QALY) gained. The majority of simulations (93.3%) were below the commonly accepted willingness-to-pay threshold of AUD $50,000 per QALY gained in Australia. Sensitivity analyses indicated that the base-case results were robust. CONCLUSIONS In this first cost-effectiveness analysis of HCL technologies for the management of young people with type 1 diabetes, HCL therapy was found to be cost-effective compared with current care in Australia.

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Section: Mean (Low Inputhigh Input) Values * For the Variables In Sup...mentioning

confidence: 99%

The Cost of Control: Cost-effectiveness Analysis of Hybrid Closed-Loop Therapy in Youth

et al. 2022

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“…A recent systematic review and network meta‐analysis (14 studies, 1,043 participants) has compared eight technologies used in type 1 diabetes (excluding pregnancy) using randomised controlled trials ≥2 weeks of duration. Closed‐loop systems led to greater percent time in range 3.9–10.0 mmol/L (70–180 mg/dl) than any other management strategy with mean percent time in range 17.85 (95% predictive interval: 7.56–28.14) longer than with usual care of multiple daily injections with capillary glucose testing 33 …”

Section: Evolution Of Closed‐loop Testing and Studiesmentioning

confidence: 92%

“…Closed-loop systems led to greater percent time in range 3.9-10.0 mmol/L (70-180 mg/dl) than any other management strategy with mean percent time in range 17.85 (95% predictive interval: 7.56-28.14) longer than with usual care of multiple daily injections with capillary glucose testing. 33 Further systematic review and network meta-analysis including randomised controlled trials ≥6 weeks duration in adults with type 1 diabetes excluding pregnancy (52 studies compared, comprising 3,975 participants) compared 12 diabetes management technologies. Integrated insulin pump and continuous glucose monitoring (CGM) systems with low-glucose suspend or hybrid closed-loop algorithms resulted in A 1c levels 0.96% (predictive interval [95% CI: 0.04-1.89]) and 0.87% (95% CI: 0.12-1.63) lower than multiple daily injections with either flash glucose monitoring or capillary glucose testing, respectively.…”

Section: Systematic Reviews and Metaanalysesmentioning

confidence: 99%

Automated insulin dosing systems: Advances after a century of insulin

2021

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The daily complexities of insulin therapy and glucose variability in type 1 diabetes still pose significant challenges, despite advancements in modern insulin analogues. Minimising hypoglycaemia and optimising time spent within target glucose range are recommended to reduce the risk of diabetes‐related complications and distress. Access to structured education and adjuvant diabetes technologies, such as insulin pumps and glucose sensors, are recommended by National Institute for Health and Care Excellence (NICE) to enable people with type 1 diabetes achieve their glycaemic goals. One hundred years after the discovery of insulin, automated insulin dosing (AID, a.k.a. closed loop or artificial pancreas) systems are a reality with a number of systems available and being used in usual clinical practice. Evidence from randomised clinical trials and real‐world prospective studies support efficacy, effectiveness and safety of AID systems. Qualitative evaluations reveal treatment satisfaction and positive effects on quality of life. Current insulin‐only AID systems still require carbohydrate and activity announcement (hybrid closed loop) due to the inherent pharmacokinetic limitations of rapid‐acting insulin analogies. Ultra‐rapid acting insulin and adjunctive use of other therapies (e.g. glucagon, pramlitide) are being evaluated to achieve full closed loop. Open‐source AID (OS‐AID) systems have been developed by the diabetes community, driven by a desire for safety and to accelerate technological advancement. In addition to effectiveness and safety, real‐world prospective studies suggest that OS‐AID systems fulfil unmet needs of commercially approved systems. The development, ongoing challenges and expectations of AID are outlined in this review.

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“…To overcome the potential risk of error when estimating average glucose from measured A1C, when feasible clinicians can use recent CGM data to document time above and below target range prior to lowering an individual's A1C target. In addition, CGM allows estimation of time in range and, in particular within close-loop systems, minimization of hypoglycemia and hyperglycemic excursions (50). A1C and CGM-derived measures provide complementary assessments of glucose control.…”

Section: A1c and Continuous Glucose Monitoring As Measures Of Glycemic Controlmentioning

confidence: 99%

The Evolution of Hemoglobin A1c Targets for Youth With Type 1 Diabetes: Rationale and Supporting Evidence

et al. 2021

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The American Diabetes Association 2020 Standards of Medical Care in Diabetes (Standards of Care) recommends a hemoglobin A1c (A1C) of <7% (53 mmol/mol) for many children with type 1 diabetes (T1D), with an emphasis on target personalization. A higher A1C target of <7.5% may be more suitable for youth who cannot articulate symptoms of hypoglycemia or have hypoglycemia unawareness and for those who do not have access to analog insulins or advanced diabetes technologies or who cannot monitor blood glucose regularly. Even less stringent A1C targets (e.g., <8%) may be warranted for children with a history of severe hypoglycemia, severe morbidities, or short life expectancy. During the “honeymoon” period and in situations where lower mean glycemia is achievable without excessive hypoglycemia or reduced quality of life, an A1C <6.5% may be safe and effective. Here, we provide a historical perspective of A1C targets in pediatrics and highlight evidence demonstrating detrimental effects of hyperglycemia in children and adolescents, including increased likelihood of brain structure and neurocognitive abnormalities, microvascular and macrovascular complications, long-term effects, and increased mortality. We also review data supporting a decrease over time in overall severe hypoglycemia risk for youth with T1D, partly associated with the use of newer insulins and devices, and weakened association between lower A1C and severe hypoglycemia risk. We present common barriers to achieving glycemic targets in pediatric diabetes and discuss some strategies to address them. We aim to raise awareness within the community on Standards of Care updates that impact this crucial goal in pediatric diabetes management.

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Time in range for multiple technologies in type 1 diabetes: a systematic review and network meta-analysis

Cited by 8 publications

References 0 publications

The Cost of Control: Cost-effectiveness Analysis of Hybrid Closed-Loop Therapy in Youth

The Cost of Control: Cost-effectiveness Analysis of Hybrid Closed-Loop Therapy in Youth

Automated insulin dosing systems: Advances after a century of insulin

The Evolution of Hemoglobin A1c Targets for Youth With Type 1 Diabetes: Rationale and Supporting Evidence

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