Cost-effectiveness of second-line antihyperglycemic therapy in patients with type 2 diabetes mellitus inadequately controlled on metformin
Bibliographic record
Abstract
BACKGROUND: Metformin is widely accepted as first-line pharmacotherapy for patients with type 2 diabetes mellitus when glycemic control cannot be achieved by lifestyle interventions alone. However, uncertainty exists regarding the optimal second-line therapy for patients whose diabetes is inadequately controlled by metformin monotherapy. Increased use of newer, more costly agents, along with the rising incidence of type 2 diabetes, carries significant budgetary implications for health care systems. We conducted this analysis to determine the relative costs, benefits and cost-effectiveness of options for second-line treatment of type 2 diabetes. METHODS: We used the United Kingdom Prospective Diabetes Study Outcomes Model to forecast diabetes-related complications, quality-adjusted life-years and costs of alternative second-line therapies available in Canada for adults with type 2 diabetes inadequately controlled by metformin. We obtained clinical data from a systematic review and mixed treatment comparison meta-analysis, and we obtained information on costs and utilities from published sources. We performed extensive sensitivity analyses to test the robustness of results to variation in inputs and assumptions. RESULTS: Sulphonylureas, when added to metformin, were associated with the most favourable cost-effectiveness estimate, with an incremental cost of $12 757 per quality-adjusted life-year gained, relative to continued metformin monotherapy. Treatment with other agents, including thiazolidinediones and dipeptidyl peptidase-4 inhibitors, had unfavourable cost-effectiveness estimates compared with sulphonylureas. These results were robust to extensive sensitivity analyses. INTERPRETATION: For most patients with type 2 diabetes that is inadequately controlled with metformin monotherapy, the addition of a sulphonylurea represents the most cost-effective second-line therapy.
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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 | 0.007 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".