Cost-effectiveness analysis of biologics for the treatment of chronic rhinosinusitis with nasal polyps in Canada
Bibliographic record
Abstract
Abstract Background Dupilumab, omalizumab, and mepolizumab are the three biologics currently approved for use in CRSwNP in Canada. Despite evidence of efficacy, their cost-effectiveness, which is a key factor influencing prescribing patterns, has not yet been compared to each other. Methods A cost-effectiveness model using quality-adjusted life years (QALYs) was constructed using a Decision Tree Markov analysis. A third-party healthcare payer perspective and a 10-year time horizon was used. A willingness-to-pay (WTP) threshold of 50,000 Canadian dollars (CAD) per QALY was used to determine cost-effectiveness. Dupilumab, omalizumab, and mepolizumab were each compared to each other. Results Omalizumab was the most cost-effective biologic using current estimates of cost and efficacy in CRSwNP. Using omalizumab as a baseline, dupilumab had an ICER of $235,305/QALY. Mepolizumab was dominated by omalizumab and dupilumab at the current drug prices and estimates of efficacy. Sensitivity analyses determined that when increasing the WTP threshold to $150,000/QALY, dupilumab became cost-effective compared to omalizumab in 22.5% of simulation scenarios. Additionally, altering dosing frequency had a significant effect on cost-effectiveness. Conclusion When comparing the relative cost-effectiveness of biologics in recalcitrant CRSwNP, omalizumab currently appears to be the most cost-effective option. Future reductions in drug prices, adjustments to currently approved dosing regimens, better patient selection, and improvements in sinus surgery outcomes will challenge the current cost-effectiveness models and necessitate reassessment as treatments for CRSwNP continue to evolve.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".