Cost-effectiveness of Canagliflozin versus Sitagliptin When Added to Metformin and Sulfonylurea in Type 2 Diabetes in Canada.
Bibliographic record
Abstract
BackgroundCanagliflozin, an agent that inhibits sodium glucose co-transporter 2, is approved as add-on to metformin plus sulfonylurea for the treatment of type 2 diabetes in Canada. Canagliflozin offers greater glycemic control, as well as important additional benefits such as weight loss and blood pressure reductions, versus dipeptidyl peptidase-4 inhibitors such as sitagliptin. ObjectiveThis analysis evaluated the cost-effectiveness of canagliflozin 300 mg and canagliflozin 100 mg versus sitagliptin 100 mg in patients with type 2 diabetes inadequately controlled on metformin plus sulfonylurea from the perspective of the Canadian Agency for Drugs and Technologies in Health. MethodsA 40-year cost-effectiveness analysis was performed using the validated Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM). Patient characteristics, treatment effects, and rates of hypoglycemia and adverse events were sourced from the canagliflozin clinical program. Canada-specific costs and utilities were applied. Sensitivity analyses were conducted using alternative values for key model inputs. ResultsBoth canagliflozin 300 and 100 mg dominated sitagliptin 100 mg over 40 years, providing quality-adjusted life-year gains of 0.31 and 0.28, and cost offsets of $2,217 and $2,560, respectively. Both canagliflozin doses dominated sitagliptin in each of the sensitivity analyses. ConclusionsSimulation results suggested that canagliflozin 300 and 100 mg provided better health outcomes and lower costs than sitagliptin 100 mg as a third-line therapy added-on to metformin and sulfonylurea in patients with type 2 diabetes in Canada.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".