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Published on: June 11, 2012
Cost-Utility Analysis of Control-IQ Technology Relative to Conventional Insulin Therapy in Adults with Type 1
Jolien De Meulemeester1, Francesca Fiorentino2, Nuno Picado3
1Department of Endocrinology, University Hospitals Leuven - KU Leuven, Leuven, Belgium.
Objective:
This study evaluated the cost utility of the t:slim X2 insulin pump with Control-IQ technology (Control-IQ) relative to multiple daily injections (MDIs) and standard insulin pump therapy, both used in combination with continuous glucose monitoring (CGM), in adults with type 1 diabetes from a payer perspective in Belgium.
Research Design And Methods:
A lifetime cost-utility analysis was conducted using the IQVIA CORE Diabetes Model. Baseline characteristics and treatment effects were informed by the Belgian real-world, multicenter, prospective INRANGE study. Direct medical costs included treatment, complication management, and severe hypoglycemic events. Country-specific costs were based on RIZIV-INAMI data and other publicly available sources. Utility values were based on published literature and included the reduction in fear of hypoglycemia associated with Control-IQ as reported in the INRANGE study. Outcomes included quality-adjusted life years (QALYs) and incremental cost-utility ratios (ICURs). Scenario analyses explored variations in the comparator (MDI + CGM only), reduced HbA1c efficacy, and time horizon.
Results:
Control-IQ yielded 19.50 QALYs versus 17.92 for MDI and standard insulin pump therapy plus CGM, with total costs of €193,588 and €160,129, respectively, resulting in an ICUR of €21,111/QALY. Scenario analyses confirmed robustness: MDI + CGM as sole comparator (ICUR: €41,701/QALY), reduced HbA1c efficacy (ICUR: €25,967/QALY), and a 20-year time horizon (ICUR: €30,183/QALY).
Conclusions:
Control-IQ provides clinical benefits relative to MDI and standard insulin pump therapy plus CGM in adults with type 1 diabetes in Belgium and appears to be cost-effective in this setting, considering commonly used thresholds. These findings support the broader adoption of automated insulin delivery systems in diabetes management.
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