Patient costs associated with external beam radiotherapy treatment for localized prostate cancer: the benefits of hypofractionated over conventionally fractionated radiotherapy.
Bibliographic record
Abstract
INTRODUCTION: To estimate the out-of-pocket costs for patients undergoing external beam radiotherapy (EBRT) for prostate cancer and calculate the patient-related savings of being treated with a 5-fraction versus a standard 39-fraction approach. MATERIALS AND METHODS: Seventy patients accrued to the pHART3 (n = 84) study were analyzed for out-of-pocket patient costs as a result of undergoing treatment. All costs are in Canadian dollars. Using the postal code of the patient's residence, the distance between the hospital and patient home was found using Google Maps. The Canada Revenue Agency automobile allowance rate was then applied to determine the cost per kilometer driven. RESULTS: The average cost of travel from the hospital and pHART3 patient's residence was $246 per person after five trips. In a standard fractionation regimen, pHART3 patients would have incurred an average cost of $1921 after 39 visits. The patients receiving hypofractionated radiotherapy would have paid an average of $38 in parking while those receiving conventional treatment would have paid $293. The difference in out-of-pocket costs for the patients receiving a standard versus hypofractionated treatment was $1930. CONCLUSIONS: Medium term prospective data shows that hypofractionated radiotherapy is an effective treatment method for localized prostate cancer. Compared to standard EBRT, hypofractionated radiotherapy requires significantly fewer visits. Due to the long distance patients may have to travel to the cancer center and the expense of parking, the short course treatment saves each patient an average of $1900. A randomized study of standard versus hypofractionated accelerated radiotherapy should be conducted to confirm a favorable efficacy and tolerability profile of the shorter fractionation scheme.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".