A systematic review and meta-analysis to evaluate the influence of surgical method on specimen margins and biochemical recurrence after radical prostatectomy for high-risk prostate cancer.
Bibliographic record
Abstract
65 Background: To date there is no robust evidence comparing the outcomes of robotic and open radical prostatectomies in patients with high-risk prostate cancer. The purpose of this study is to perform a meta-analysis comparing the rates of positive surgical margins (PSM) and biochemical recurrence (BCR) between open radical prostatectomy (ORP) and robot-assisted radical prostatectomy (RARP) in patients with high-risk prostate cancer. Methods: A systematic review was performed on Pubmed, Embase and Scopus databases in August 2016, according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) statement. References retrieved were evaluated using the Newcastle-Ottawa scale and the Black and Down’s tool for quality assessment. Nine retrospective cohorts comparing ORP and RARP were selected and included in the meta-analysis. Results: Nine studies reported the PSMs. Patients treated with RARP presented less risk of PSMs (risk difference -0.04, p 0.02) than those treated with ORP. Five articles reported hazard ratios for BCR-free survival. Patients treated with RARP had less risk of BCR (HR 0.72, 95% CI 0.58-0.89) than those treated with ORP. Reports for PSM assessment were considered of adequate quality, while the studies retrieved for BCR assessment were considered limited because of the heterogeneity of their results. Conclusions: Patients with high-risk prostate cancer treated with RARP have less risk of having PSM and BCR when compared to those treated with ORP. A strong conclusion is precluded due to the observational nature of the studies retrieved for our analysis.
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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 | 0.019 | 0.045 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.052 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".