Addition of continuous glucose monitoring to glucagon-like peptide 1 receptor agonist treatment for type 2 diabetes mellitus – An economic evaluation
Bibliographic record
Abstract
BACKGROUND: Both glucagon-like peptide 1 receptor agonists (GLP-1 RAs) and continuous glucose monitoring (CGM) have been shown to improve glycated hemoglobin A1c (A1c) levels among patients with type 2 diabetes mellitus (T2DM). Recently, a US real-world study found statistically significant improvements in A1c levels among patients using GLP-1 RA and a CGM device, compared with a matched cohort receiving only GLP-1 RA. OBJECTIVES: To assess the cost-effectiveness from a US payer perspective of initiating CGM (FreeStyle Libre Systems) in people living with T2DM using a GLP-1 RA therapy, compared with GLP-1 RA alone. METHODS: A patient-level microsimulation model was run for 10,000 patients over a lifetime horizon with 3.0% discounting for costs and utilities. Patient characteristics were based on the overall population of the US real-world study and the subgroup of patients not using intensive insulin. The effect of CGM was modeled as a persistent reduction in A1c compared with GLP-1 RA alone (overall = 0.37%; patients not using intensive insulin = 0.34%). Costs ($2,023) and disutilities were applied to diabetes complications and acute diabetic events. Outcomes were assessed as quality-adjusted life years (QALYs). RESULTS: The base-case incremental cost-effectiveness ratio (incremental costs/incremental QALYs) for GLP-1 RA plus CGM vs GLP-1 RA alone was $40,968/QALY in the overall cohort (cost = $484,180 vs $473,938; QALYs = 13.37 vs 13.12). Among patients not using intensive insulin, the incremental cost-effectiveness ratio was $43,095/QALY. Scenario analysis showed that the model results were robust to changing assumptions. Probabilistic sensitivity analysis showed that GLP-1 RA plus CGM had a 64% probability of being cost-effective at a willingness-to-pay threshold of $100,000 per QALY. CONCLUSIONS: From a US payer perspective, CGM is cost-effective when added to GLP-1 RA therapies for the treatment of T2DM, including for patients not using intensive insulin.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".