Radiation Costing Methods: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: Costs for radiation therapy (rt) and the methods used to cost rt are highly diverse across the literature. To date, no study has compared various costing methods in detail. Our objective was to perform a thorough review of the radiation costing literature to identify sources of costs and methods used. METHODS: A systematic review of Ovid medline, Ovid oldmedline, embase, Ovid HealthStar, and EconLit from 2005 to 23 March 2015 used search terms such as "radiation," "radiotherapy," "neoplasm," "cost," " cost analysis," and "cost benefit analysis" to locate relevant articles. Original papers were reviewed for detailed costing methods. Cost sources and methods were extracted for papers investigating rt modalities, including three-dimensional conformal rt (3D-crt), intensity-modulated rt (imrt), stereotactic body rt (sbrt), and brachytherapy (bt). All costs were translated into 2014 U.S. dollars. RESULTS: Most of the studies (91%) reported in the 33 articles retrieved provided rt costs from the health system perspective. The cost of rt ranged from US$2,687.87 to US$111,900.60 per treatment for imrt, followed by US$5,583.28 to US$90,055 for 3D-crt, US$10,544.22 to US$78,667.40 for bt, and US$6,520.58 to US$19,602.68 for sbrt. Cost drivers were professional or personnel costs and the cost of rt treatment. Most studies did not address the cost of rt equipment (85%) and institutional or facility costs (66%). CONCLUSIONS: Costing methods and sources were widely variable across studies, highlighting the need for consistency in the reporting of rt costs. More work to promote comparability and consistency across studies is needed.
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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 | 0.032 | 0.162 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.016 |
| Bibliometrics | 0.026 | 0.023 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".