Hypofractionated Radiation Therapy for Localized Prostate Cancer: An ASTRO, ASCO, and AUA Evidence-Based Guideline
Bibliographic record
Abstract
The aim of this guideline is to present recommendations regarding moderately hypofractionated (240-340 cGy per fraction) and ultrahypofractionated (500 cGy or more per fraction) radiation therapy for localized prostate cancer.The American Society for Radiation Oncology convened a task force to address 8 key questions on appropriate indications and dose-fractionation for moderately and ultrahypofractionated radiation therapy, as well as technical issues, including normal tissue dose constraints, treatment volumes, and use of image guided and intensity modulated radiation therapy. Recommendations were based on a systematic literature review and created using a predefined consensus-building methodology and Society-approved tools for grading evidence quality and recommendation strength.Based on high-quality evidence, strong consensus was reached for offering moderate hypofractionation across risk groups to patients choosing external beam radiation therapy. The task force conditionally recommends ultrahypofractionated radiation may be offered for low- and intermediate-risk prostate cancer but strongly encourages treatment of intermediate-risk patients on a clinical trial or multi-institutional registry. For high-risk patients, the task force conditionally recommends against routine use of ultrahypofractionated external beam radiation therapy. With any hypofractionated approach, the task force strongly recommends image guided radiation therapy and avoidance of nonmodulated 3-dimensional conformal techniques.Hypofractionated radiation therapy provides important potential advantages in cost and convenience for patients, and these recommendations are intended to provide guidance on moderate hypofractionation and ultrahypofractionation for localized prostate cancer. The limits in the current evidentiary base-especially for ultrahypofractionation-highlight the imperative to support large-scale randomized clinical trials and underscore the importance of shared decision making between clinicians and patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".