The role of salvage brachytherapy for local relapse after external beam radiotherapy for prostate cancer
Bibliographic record
Abstract
Prostate cancer is the most prevalent cancer amongst men. For localized disease, there currently exist several reliable treatment modalities including surgery, radiotherapy and brachytherapy. Our growing understanding of this disease indicates that local control plays a very important role in prevention of subsequent dissemination. Many improvements to external beam radiotherapy over recent years have decreased toxicity and improved outcomes, but nonetheless, local relapse remains common. Many salvage options exist for locally recurrent prostate cancer, but are rarely offered, partly because of the fear of toxicity. Many men with isolated local recurrence therefore do not receive potentially curative second line treatment and are instead treated with palliative androgen suppression. Selection plays an important role in determining which individuals are likely to benefit from salvage. Those at high risk of pre-existing micro-metastatic disease despite negative staging scans are unlikely to benefit. Prostate brachytherapy has evolved over the more than 3 decades of experience. Modern techniques allow more precise tumor localization and dose delivery. Better understanding of dosimetric parameters can distinguish optimal from suboptimal implants. Salvage brachytherapy can be an effective treatment for locally recurrent prostate cancer after prior external beam radiotherapy. We review the literature pertaining to both low dose rate (LDR) and high dose rate (HDR) salvage brachytherapy and discuss patient selection, optimal dose, treatment volume and toxicity avoidance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".