Cost–Utility Analysis of Radiation Treatment Modalities for Intermediate-Risk Prostate Cancer
Bibliographic record
Abstract
INTRODUCTION: Variable costs of different radiation treatment modalities have played an important factor in selecting the most appropriate treatment for patients with intermediate-risk prostate cancer. METHODS: Analysis using a Markov model was conducted to simulate 20-year disease trajectory, quality-adjusted life years (QALYs) and health system costs of a cohort of intermediate-risk prostate cancer patients with mean age of 60 years. Clinical outcomes on toxicity and disease recurrence were measured and a probabilistic sensitivity analysis was performed, varying input parameters simultaneously according to their distributions. RESULTS: Among the six radiation treatment modalities, including conventionally fractionated intensity-modulated radiation therapy (IMRT), hypofractionated IMRT, IMRT combined with high-dose-rate (HDR) brachytherapy, HDR brachytherapy monotherapy, low-dose-rate brachytherapy monotherapy, and stereotactic body radiotherapy (SBRT), SBRT was found to be more cost-effective when compared with LDR-b and other treatment modalities, resulting in an incremental cost-utility ratio of $2985 per QALY. CONCLUSIONS: Stereotactic body radiotherapy is the most cost-effective radiation treatment modality in treatment of intermediate-risk prostate cancer, while treatment toxicity and cost data are the key drivers of the cost-utility. Further work is required with long-term follow-up for SBRT.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".