Cost-Effectiveness of Everolimus for the Treatment of Advanced Neuroendocrine Tumours of Gastrointestinal or Lung Origin in Canada
Bibliographic record
Abstract
BACKGROUND: In 2016, everolimus was approved by Health Canada for the treatment of unresectable, locally advanced or metastatic, well-differentiated, non-functional, neuroendocrine tumours (NET) of gastrointestinal (GI) or lung origin in adult patients with progressive disease. This analysis evaluated the cost-effectiveness of everolimus in this setting from a Canadian societal perspective. METHODS: A partitioned survival model was developed to compare the cost per life-year (LY) gained and cost per quality-adjusted life-year (QALY) gained of everolimus plus best supportive care (BSC) versus BSC alone in patients with advanced or metastatic NET of GI or lung origin. Model health states included stable disease, disease progression, and death. Efficacy inputs were based on the RADIANT-4 trial and utilities were mapped from quality-of-life data retrieved from RADIANT-4. Resource utilization inputs were derived from a Canadian physician survey, while cost inputs were obtained from official reimbursement lists from Ontario and other published sources. Costs and efficacy outcomes were discounted 5% annually over a 10-year time horizon, and sensitivity analyses were conducted to test the robustness of the base case results. RESULTS: Everolimus had an incremental gain of 0.616 QALYs (0.823 LYs) and CA$89,795 resulting in an incremental cost-effectiveness ratio of CA$145,670 per QALY gained (CA$109,166 per LY gained). The probability of cost-effectiveness was 52.1% at a willingness to pay (WTP) threshold of CA$150,000 per QALY. CONCLUSIONS: Results of the probabilistic sensitivity analysis indicate that everolimus has a 52.1% probability of being cost-effective at a WTP threshold of CA$150,000 per QALY gained in Canada.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".