Cost effectiveness of positron emission tomography in Canada.
Bibliographic record
Abstract
BACKGROUND: Positron emission tomography (PET) has been shown to be cost effective for the staging of stage I and II breast cancer, recurrent colorectal cancer and non small cell lung cancer. This study determines a required catchment size for the management of these three cancers based on a breakeven analysis. MATERIAL/METHODS: Cost effectiveness analysis is used to determine the cost savings of introducing PET into the diagnostic algorithm for the staging of stage I and II breast cancer, recurrent colorectal cancer and non small cell lung cancer. The cost savings for these cancers are used to calculate a required catchment area for the installation of a PET center with cyclotron. RESULTS: The aggregate estimated "breakeven" cost of a PET study would be dollars 2195, well below the expected cost per study. In order to break even, each PET device would require 740 new cases per year. For a general representative population, one person per 766 may benefit from a PET scan if a PET study was included in the diagnostic algorithm for all three cancers. Finally, a calculated catchment size of 567,000 people would support the use of a PET center with cyclotron CONCLUSIONS: The use of PET for the staging of cancer appears to be cost effective in most jurisdictions in Canada.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".