Salvage versus primary robot-assisted radical prostatectomy: a propensity-matched comparative effectiveness study from a high-volume tertiary centre
Bibliographic record
Abstract
Introduction Salvage Robot-Assisted Radical Prostatectomy (sRARP) is a potential treatment option for locally recurrent Prostate Cancer after non-surgical primary treatment. There are minimal data comparing outcomes between similar-risk, propensity-matched salvage and primary Robot-Assisted Radical Prostatectomy (RARP). We compare perioperative, oncological and functional outcomes of sRARP with primary RARP and between sRARP post-whole and focal gland therapy. Methods 1:1 propensity-matched comparison of 146 sRARP with primary RARP from a cohort of 3,852 consecutive patients from a high-volume tertiary centre. Results There were no significant differences in patient characteristics between the salvage and primary RARP groups. Grade III-V Clavien-Dindo complication rates were 1.3% and 0% in the salvage and primary groups (p=0.310). Median (IQR) follow-up was 16 (10, 30) and 21 (13, 33) months in the salvage and primary groups. BCR rates were 30.8% and 13.7% in the salvage and primary groups (p<0.001). Pad-free continence rates were 79.1% and 85.4% at two years in the salvage and primary groups (p=0.160). Erectile dysfunction was 95.2% and 77.4% in the salvage and primary groups (p<0.001). On comparison of whole and focal gland groups, biochemical recurrence was 33.3% and 29.1% (p=0.687), pad-free continence rates were 66% and 89.3% (p=0.001), and ED rates were 98.3% and 93% (p=0.145). Conclusions SRARP has similar perioperative but inferior oncological outcomes to primary RARP. Continence rates are similar to primary RARP, but potency is worse. Perioperative and oncological outcomes of sRARP after focal gland therapy are similar compared to after whole gland therapy but continence outcomes are superior.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".