The cost‐effectiveness of cystic fibrosis transmembrane conductance regulator modulators: A systematic review of economic evaluations
Bibliographic record
Abstract
Cystic fibrosis (CF) is a life-threatening genetic disorder affecting approximately 160 000 people worldwide. Mutations in the CF transmembrane conductance regulator (CFTR) gene cause progressive multi-organ damage, particularly in the lungs. CFTR modulators have transformed CF care; however, their high costs raise concerns about cost-effectiveness. This systematic review examined cost-effectiveness studies of four CFTR modulators: ivacaftor (IVA), lumacaftor-ivacaftor (LUM-IVA), tezacaftor-ivacaftor (TEZ-IVA) and elexacaftor-tezacaftor-ivacaftor (ELX-TEZ-IVA). Ovid MEDLINE, Embase and government websites were searched for studies comparing modulators with standard care or each other. Study quality was assessed using the Consensus on Health Economic Criteria (CHEC) checklist and reporting quality using CHEERS 2022. A narrative synthesis was conducted and incremental cost-effectiveness ratios (ICERs) were discussed. The review followed PRISMA guidelines and was registered with PROSPERO (CRD42024570006). Twenty-nine studies yielded 34 ICERs (cost per quality-adjusted life-year [QALY] gained) across Canada, England, Ireland, Scotland, Wales and the United States. CFTR modulators produced significant clinical benefits, including improved QALYs and reduced pulmonary exacerbations, but were associated with extremely high costs, exceeding willingness-to-pay thresholds. IVA's ICERs ranged from US$536 472/QALY in Scotland to US$4 898 079/QALY in Canada, LUM-IVA's from US$378 503/QALY in Scotland to US$7 504 825/QALY in Canada, TEZ-IVA's from US$635 325/QALY in Scotland to US$1 657 332/QALY in the United States and ELX-TEZ-IVA's from US$334 047/QALY in Ireland to US$2 093 361/QALY in Canada. Sensitivity analyses indicated the need for substantial price reductions to be considered cost-effective. CFTR modulators provide substantial health benefits but pose significant financial challenges. Future research should broaden economic evaluations, consider societal impacts and explore strategies to improve affordability and access.
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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 | 0.019 | 0.086 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".