Boosting imaging defined dominant prostatic tumors: A systematic review
Bibliographic record
Abstract
INTRODUCTION: Dominant cancer foci within the prostate are associated with sites of local recurrence post radiotherapy. In this systematic review we sought to address the question: "what is the clinical evidence to support differential boosting to an imaging defined GTV volume within the prostate when delivered by external beam or brachytherapy". MATERIALS AND METHODS: A systematic review was conducted to identify clinical series reporting the use of radiation boosts to imaging defined GTVs. RESULTS: Thirteen papers describing 11 unique patient series and 833 patients in total were identified. Methods and details of GTV definition and treatment varied substantially between series. GTV boosts were on average 8 Gy (range 3-35 Gy) for external beam, or 150% for brachytherapy (range 130-155%) and GTV volumes were small (<10 ml). Reported toxicity rates were low and may reflect the modest boost doses, small volumes and conservative DVH constraints employed in most studies. Variability in patient populations, study methodologies and outcomes reporting precluded conclusions regarding efficacy. CONCLUSIONS: Despite a large cohort of patients treated differential boosts to imaging defined intra-prostatic targets, conclusions regarding optimal techniques and/or efficacy of this approach are elusive, and this approach cannot be considered standard of care. There is a need to build consensus and evidence. Ongoing prospective randomized trials are underway and will help to better define the role of differential prostate boosts based on imaging defined GTVs.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".