Cost-Effectiveness of Once-Weekly Semaglutide 1 mg versus Canagliflozin 300 mg in Patients with Type 2 Diabetes Mellitus in a Canadian Setting
Bibliographic record
Abstract
OBJECTIVE: Our objective was to evaluate the long-term cost-effectiveness of once-weekly semaglutide 1 mg versus once-daily canagliflozin 300 mg in patients with type 2 diabetes mellitus (T2DM) uncontrolled with metformin from the healthcare payer and societal perspectives in Canada. METHODS: Head-to-head data from the SUSTAIN 8 randomised trial (NCT03136484) were extrapolated over 40 years using economic simulation modelling. The cost-effectiveness of once-weekly semaglutide 1 mg versus canagliflozin 300 mg for treating T2DM was estimated using the Swedish Institute for Health Economics-Diabetes Cohort Model (IHE-DCM) and the Economic and Health Outcomes Model of T2DM (ECHO-T2DM). Unit costs and disutility weights capturing treatments and key macro- and microvascular complications were sourced from the literature to best match the Canadian setting. A probabilistic base-case simulation and sensitivity analyses were conducted. RESULTS: Once-weekly semaglutide 1 mg was associated with reductions in macro- and microvascular complications, yielding incremental cost-effectiveness ratios (ICERs) of (Canadian dollars [CAD]) CAD16,392 and 18,098 per incremental quality-adjusted life-year (QALY) gained versus canagliflozin 300 mg for IHE-DCM and ECHO-T2DM, respectively, from a healthcare payer perspective. Accounting for productivity loss as well, ICERs were CAD14,127 and 13,188 per QALY gained for IHE-DCM and ECHO-T2DM, respectively, from a societal perspective. Sensitivity analyses confirmed that the base-case results were robust to changes in input parameters and assumptions used. CONCLUSIONS: At a willingness-to-pay threshold of CAD50,000 per QALY gained, once-weekly semaglutide 1 mg was cost-effective over 40 years versus once-daily canagliflozin 300 mg for the treatment of T2DM in patients failing to maintain glycemic control with metformin alone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".