Estimating the Costs of Intensity-Modulated and 3-Dimensional Conformal Radiotherapy in Ontario
Bibliographic record
Abstract
BACKGROUND: Radiotherapy is a common treatment for many cancers, but up-to-date estimates of the costs of radiotherapy are lacking. In the present study, we estimated the unit costs of intensity-modulated radiotherapy (imrt) and 3-dimensional conformal radiotherapy (3D-crt) in Ontario. METHODS: An activity-based costing model was developed to estimate the costs of imrt and 3D-crt in prostate cancer. It included the costs of equipment, staff, and supporting infrastructure. The framework was subsequently adapted to estimate the costs of radiotherapy in breast cancer and head-and-neck cancer. We also tested various scenarios by varying the program maturity and the use of volumetric modulated arc therapy (vmat) alongside imrt. RESULTS: From the perspective of the health care system, treating prostate cancer with imrt and 3D-crt respectively cost $12,834 and $12,453 per patient. The cost of radiotherapy ranged from $5,270 to $14,155 and was sensitive to analytic perspective, radiation technique, and disease site. Cases of head-and-neck cancer were the most costly, being driven by treatment complexity and fractions per treatment. Although imrt was more costly than 3D-crt, its cost will likely decline over time as programs mature and vmat is incorporated. CONCLUSIONS: Our costing model can be modified to estimate the costs of 3D-crt and imrt for various disease sites and settings. The results demonstrate the important role of capital costs in studies of radiotherapy cost from a health system perspective, which our model can accommodate. In addition, our study established the need for future analyses of imrt cost to consider how vmat affects time consumption.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".