<p>Cost-Effectiveness Analysis of a Once-Daily Single-Inhaler Triple Therapy for Patients with Chronic Obstructive Pulmonary Disease (COPD) Using the FULFIL Trial: A Spanish Perspective</p>
Bibliographic record
Abstract
Purpose: To evaluate the cost-effectiveness of once-daily fluticasone furoate/umeclidinium/vilanterol (FF/UMEC/VI) vs twice-daily budesonide/formoterol (BUD/FOR) in patients with symptomatic chronic obstructive pulmonary disease (COPD) at risk of exacerbations, from the Spanish National Healthcare System perspective. Patients and Methods: The validated GALAXY-COPD model was used to simulate disease progression and predict healthcare costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) over a 3-year time horizon for a Spanish population. Patient characteristics from published literature were supplemented by data from FULFIL (NCT02345161), which compared FF/UMEC/VI vs BUD/FOR in patients with symptomatic COPD at risk of exacerbations. Treatment effects, extrapolated to 3 years, were based on Week 24 results in the FULFIL intent-to-treat population, including change in forced expiratory volume in 1 second, St. George's Respiratory Questionnaire score, and exacerbation rates. Treatment, exacerbations, and COPD management costs (2019€) were informed by Spanish public sources and published literature. A 3% discount rate for costs and benefits was applied. One-way sensitivity and scenario analyses, and probabilistic sensitivity analysis (PSA), were performed. Results: FF/UMEC/VI treatment led to fewer moderate and severe exacerbations (2.126 and 0.306, respectively) vs BUD/FOR (2.608 and 0.515, respectively), with a mean incremental cost of €69 and gain of 0.107 QALYs, which resulted in an ICER of €642 per QALY gained. In sensitivity analyses, the ICER was most sensitive to treatment effect variations in exacerbations and healthcare resource utilization/event costs. Overall, 95% of 1000 PSA simulations resulted in an ICER less than €11,000 per QALY gained for FF/UMEC/VI vs BUD/FOR, confirming robustness of the results. The probability of FF/UMEC/VI being cost-effective vs BUD/FOR was 100% at a willingness-to-pay threshold of €30,000 per QALY gained. Conclusion: At the accepted Spanish ICER threshold of €30,000, FF/UMEC/VI represents a cost-effective treatment option vs BUD/FOR in patients with symptomatic COPD at risk of exacerbations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".