The Technique and Cost of Radiosurgery for the Treatment of 1-3 Brain Metastases
Bibliographic record
Abstract
BACKGROUND: Radiosurgery can be delivered through a variety of modalities including robotic and fixed gantry Linac-based systems. They appear equally effective and safe. Thus, community need and costs remain the main determinants for choosing a given modality. We performed an economic evaluation to identify settings in which one modality could be preferred over the other. METHODS: Using local estimates of resource volumes and unit prices, we computed the incremental cost/patient of robotic radiosurgery compared to fixed-gantry radiosurgery from a payer's perspective. By varying parameters of resource volumes, we performed a probabilistic analysis stratified by number of brain lesions. in addition, we performed sensitivity analyses to examine the effect of patient volume on cost/patient. RESULTS: The cost of robotic radiosurgery was $4,783/patient, and cost of fixed-gantry radiosurgery was $5,166/patient. The mean incremental cost was $-383 (95% interval: $-670, $110) for all lesions, $78 ($23, $123) for solitary lesions, and $-610 ($-679, $-534) for multiple lesions. The cost/patient of robotic radiosurgery varied from $5,656 (low volume setting) to $4,492 (high volume setting). CONCLUSION: in settings of moderate to high volume (6-10 hours of daily operation), and in multiple lesions, robotic radiosurgery is more cost effective than fixed-gantry radiosurgery. Technique utilisée et coût de la radiochirurgie pour le traitement de 1 à 3 métastases cérébrales.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".