<scp>Cost‐effectiveness</scp> of endoscopic endonasal vs transcranial approaches for olfactory groove meningioma
Bibliographic record
Abstract
BACKGROUND: Endoscopic endonasal approaches (EEAs) have been adopted as an alternative to standard transcranial approaches for olfactory groove meningiomas (OGMs). However, the relative cost-effectiveness remains controversial. METHODS: Cost-utility analysis from a societal perspective comparing EEA vs transcranial approaches for OGM was used in this study. Surgical treatment was modeled using decision analysis, and a Markov model was adopted over a 20-year horizon. Parameters were obtained from literature review. Costs were expressed in 2017 Canadian dollars. RESULTS: In the base case, EEA was cost-effective compared with transcranial surgery with an incremental cost-effectiveness ratio of $33 523 ($30 475 USD)/QALY. There was a 55% likelihood that EEA was cost-effective at a willingness-to-pay of $50 000/QALY. EEA remained cost-effective at a cerebrospinal fluid leak rate below 60%, gross total resection rate above 25%, and base cost less than $66 174 ($60 158 USD). CONCLUSION: EEA may be a cost-effective alternative to transcranial approaches for selected OGM.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".