Economic Evaluation of Nivolumab Plus Ipilimumab Combination as First-Line Treatment for Patients with Advanced Melanoma in Canada
Bibliographic record
Abstract
OBJECTIVE: Our objective was to evaluate the cost effectiveness of the combination of nivolumab and ipilimumab, referred to as "Regimen", as a first-line treatment for patients with advanced melanoma from the perspective of Canada's public healthcare system. METHODS: We developed a partitioned-survival model (progression-free survival, post-progression survival, and death) to determine the clinical and economic outcomes of immunotherapy for advanced melanoma over a 20-year time horizon. Regimen was compared with nivolumab, ipilimumab, and pembrolizumab. Two treatment durations for pembrolizumab were considered: (1) maximum of 24 months or until progression or (2) no maximum duration, until progression. The model used data from CheckMate-067 (28 months' follow-up) for treatments involving nivolumab and ipilimumab. The efficacy of pembrolizumab was estimated using indirect comparisons. A scenario looking at the cost of subsequent treatments following disease progression was examined. RESULTS: Regimen had better outcomes and was cost effective compared with all other immunotherapies at a threshold of $CAN100,000 per quality-adjusted life-year (QALY) gained. Compared with nivolumab and ipilimumab, the incremental cost-effectiveness ratios (ICERs) were $CAN47,119 and 66,750 per QALY, respectively. Compared with pembrolizumab with a treatment duration cap, the ICER was $CAN85,436. When assuming no duration cap, Regimen dominated pembrolizumab. With the inclusion of subsequent treatment costs following progression, Regimen's ICER improved compared with all other comparators. CONCLUSIONS: Despite the advent of effective new therapies for advanced melanoma, prognosis remains poor for some patients. Compared with other immunotherapies, Regimen offers marked benefit and may be a cost-effective treatment option.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".