A critical analysis of the long-term impact of brachytherapy for prostate cancer: a review of the recent literature
Bibliographic record
Abstract
PURPOSE OF REVIEW: A number of articles have been published in the past several months providing long-term follow-up data on large brachytherapy series from centers of excellence or highly experienced individual practitioners. Our purpose is to review this recent literature and place it in context, especially as compared with notable articles in the recent past that have described less favorable outcomes. RECENT FINDINGS: A total of 3773 patients were included in three large permanent seed implant studies, the first with almost exclusively low-dose rate permanent seed brachytherapy monotherapy, the second including a large proportion of patients receiving 6 months of androgen suppression, and the third including both supplemental external beam radiotherapy (EBRT) and hormonal therapy. The 7-10 year biochemical no evidence of disease rates ranged from 94 to 95.6%, with the vast majority of patients achieving prostate specific antigen nadirs less than 0.4 ng/ml. Eight to 10 year follow-up on high-dose rate brachytherapy patients treated with combined EBRT and an high-dose rate boost are equally impressive, especially considering that these series contain a large proportion of men with unfavorable disease. SUMMARY: Both low-dose rate and high-dose rate prostate brachytherapy, either alone or given as a boost combined with moderate-dose EBRT, provide impressive long-term disease control and may be the optimal form of intraprostatic dose escalation.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".