MRI-guided focal or integrated boost high dose rate brachytherapy for recurrent prostate cancer
Bibliographic record
Abstract
Background and purpose: Locally recurrent prostate cancer after radiotherapy merits an effective salvage strategy that mitigates the risk of adverse events. We report outcomes of a cohort enrolled across two institutions investigating MRI-guided tumor-targeted salvage high dose rate brachytherapy (HDR-BT). Materials and methods: Analysis of a prospective cohort of 88 patients treated across two institutions with MRI-guided salvage HDR-BT to visible local recurrence after radiotherapy (RT). Tumor target dose ranged from 22-26 Gy, using either an integrated boost (ibBT) or focal technique (fBT), delivered in two implants over a median of 7 days. Outcome metrics included cancer control and toxicity (CTCAE). Quality of life (QoL-EPIC) was analyzed in a subset. Results: At a median follow-up of 35 months (6 -134), 3 and 5-year failure-free survival (FFS) outcomes were 67% and 49%, respectively. At 5 years, fBT was associated with a 17% cumulative incidence of local failure (LF) outside the GTV (vs. 7.8% ibBT, p=0.14), while LF within the GTV occurred in 13% (vs. 16% ibBT, p=0.81). Predictors of LF outside fBT volumes included pre-salvage PSA>7 ng/mL (p=0.03) and interval since RT less than 5 years (p=0.04). No attributable grade 3 events occurred, and ibBT was associated with a higher rate of grade 2 toxicity (p<0.001), and trend towards a larger reduction in QoL sexual domain score (p=0.07), compared to fBT. Conclusion: A tumor-targeted HDR-BT salvage approach achieved favorable cancer control outcomes. While a fBT was associated with less toxicity, it may be best suited to a subgroup with lower PSA at later recurrence. Tumor targeted dose escalation may be warranted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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".