Robot-Assisted Radical Prostatectomy for Potential Cancer Control in Patients with Metastatic Prostate Cancer
Bibliographic record
Abstract
Recently, cytoreductive prostatectomy for metastatic prostate cancer (mPCa) has been associated with improved oncological outcomes. This study was aimed at evaluating whether robot-assisted radical prostatectomy (RARP) as a form of cytoreductive prostatectomy can improve oncological outcomes in patients with mPCa. We conducted a retrospective study of twelve patients with mPCa who had undergone neoadjuvant therapy followed by RARP. The endpoints were biochemical recurrence-free survival, treatment-free survival, and de novo metastasis-free survival. At the end of the follow-up period, none of the enrolled patients had died from PCa. The 1- and 2-year biochemical recurrence-free survival rates were 83.3% and 66.7%, respectively, and treatment-free survival rates were 75.0% and 56.3%, respectively. One patient developed de novo bone metastases 6.4 months postoperatively, and castration-resistant prostate cancer 8.9 months postoperatively. After RARP, the median duration of recovery of urinary continence was 5.2 months. One patient had severe incontinence (>2 pads/day) 24 months postoperatively. RARP may be a treatment option in patients with mPCa who have achieved a serum prostate-specific antigen level < 0.2 ng/mL, and present without new lesions on imaging.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 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".