Patient-Reported Outcome Measures and Decision Regret After Salvage Radical Prostatectomy for Recurrent Prostate Cancer Following Radiotherapy or Focal Therapy
Bibliographic record
Abstract
Background/Objectives: Radical prostatectomy (RP) may be considered for recurrent prostate cancer (PCa) following primary curative-intended local therapy. The effect of different prior therapies on patient-reported outcome measures (PROMs) after RP is not well defined. Methods: Validated PROMs (SF-12, EPIC-26, Decision Regret Scale) were used to compare health-related quality of life (HRQOL) and functional status changes following salvage RP after radiotherapy (RT-sRP) or focal therapy (FT-sRP), relative to primary RP. Results: Among 26,515 RP patients who underwent RP between 2014 and 2024, 107 (0.4%) previously received radiotherapy (RT-sRP) and 98 (0.4%) previously received focal therapy (FT-sRP). Compared with primary patients before RP, only the sexual function of RT-sRP patients was lower (EPIC score, 51 vs. 75, p < 0.001). One year after RP, RT-sRP patients exhibited lower functional status in all EPIC-26 domains compared to primary RP patients, whereas FT-sRP patients did not differ significantly. For instance, the median 1 yr EPIC-26 urinary incontinence scores were 46 (RT-sRP), 86 (FT-sRP), and 92 (primary RP). In adjusted mixed model analyses, the detrimental effects of RT-sRP vs. primary RP were further validated. In contrast, no such association was observed for FT-sRP. Decision regret and severe complications were low. Conclusions: Prior FT had only a marginal effect on HRQOL and functional status following RP, while urinary continence and sexual function were lower for RT-sRP patients as compared to primary RP patients. However, from an overall PROM perspective, prior therapies did not exert a prohibitive effect that would preclude RP as a treatment option in those patients.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".