Evaluating the Cost of Bringing People with Type 2 Diabetes Mellitus to Multiple Targets of Treatment in Canada
Bibliographic record
Abstract
PURPOSE: Evidence suggests that clinical outcomes for people with type 2 diabetes mellitus can be improved through multifactorial treatment. The key challenges in the successful treatment of type 2 diabetes include maintaining tight glycemic control, minimizing the risk of hypoglycemia, controlling cardiovascular risk factors, and reducing or controlling weight. The aim of the present analysis was to evaluate the cost per patient achieving a composite clinical end point (glycosylated hemoglobin <7%, with no weight gain and no hypoglycemic events) in patients with type 2 diabetes in Quebec, Quebec, Canada, receiving liraglutide 1.2 mg, liraglutide 1.8 mg, thiazolidinedione, sulfonylurea, insulin glargine, sitagliptin, or exenatide. METHODS: The proportion of patients achieving control was taken from a meta-analysis that was based on the Phase III trial program of liraglutide. Treatment costs, estimated from a health care payer perspective, were calculated on the basis of the trials included in the meta-analysis and captured the study drug, needles, self-monitoring of blood glucose (SMBG) test strips, SMBG lancets, and other antidiabetes medications received. Cost-effectiveness in terms of cost per patient achieving the composite end point (cost of control) was evaluated with an economic model developed in Microsoft Excel. No discounting was applied to cost or clinical outcomes because these were not projected beyond a 1-year time horizon. Sensitivity analyses were performed. FINDINGS: Liraglutide 1.8 mg was associated with the lowest number needed to treat, with 3 patients needing to be treated to bring 1 patient to the composite end point. Pioglitazone was associated with the highest number needed to treat, with 17 patients requiring treatment to bring 1 patient to the composite end point. Evaluation of only annual pharmacy costs indicated that liraglutide 1.8 mg was the most costly treatment at Can$2780 per patient per year. Pioglitazone and glimepiride were associated with the lowest direct annual costs. Combining the clinical efficacy data with the annual cost of medications produced cost of control values of Can$6070 (liraglutide 1.2 mg), Can$6949 (liraglutide 1.8 mg), Can$7237 (glimepiride), Can$7704 (exenatide), Can$8297 (insulin glargine), Can$8741 (pioglitazone), and Can$9270 (sitagliptin) per patient achieving the composite end point. IMPLICATIONS: Liraglutide 1.2 mg and 1.8 mg were associated with the lowest cost of control values, driven by the high proportion of patients achieving the composite end point, which offset the higher medication costs. A relatively low cost of control value was achieved for glimepiride, driven by low acquisition costs, despite relatively few patients achieving the composite end point.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 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) | 0.004 | 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".