Protocol for a Pilot Study of the NODE Trial, a Prospective Multicentre Randomised Trial of Extended Pelvic Lymph Node Dissection for High-Risk Prostate Cancer
Bibliographic record
Abstract
Objectives To test the hypothesis that a randomised trial of extended pelvic lymph node dissection (ePLND) can recruit at a rate acceptable for a larger scale trial. To compare the following secondary endpoints between the 2 arms: the rate of protocol violations, the intraoperative and postoperative morbidity of ePLND, and complications, and to evaluate short-term oncological outcomes comparing biochemical recurrence, clinical recurrence, and survival between arms. Patients and Methods A pilot study will be undertaken at Chris O’Brien Lifehouse and Royal Prince Alfred Hospitals for the NODE trial. Twenty patients will be randomised 1:1 to radical prostatectomy with or withoutePLND. Eligible participants will have high-risk prostate cancer and will be scheduled for robotic radical prostatectomy. High-risk disease will be defined as in the 2019 NCCN guidelines (stage ≥ T3a, ISUP Grade Group ≥ 4 or PSA ≥ 20ng/mL). PSMA PET/CT staging not showing any extraprostatic disease will be required. Quality control measures to ensure consistent delivery of high-quality extended lymph node dissections are in place,and surgeons have been selected for their consistent ability to perform such procedures. Results The trial is currently underway. Conclusion On current available evidence, it is unclear if ePLND provides additional benefit over radicalprostatectomy.
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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 | 0.044 | 0.050 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.151 | 0.032 |
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".