Impact of the extent of lymph node dissection on survival outcomes in clinically lymph <scp>node‐positive</scp> bladder cancer
Bibliographic record
Abstract
OBJECTIVE: To determine the oncological impact of extended pelvic lymph node dissection (ePLND) vs standard PLND (sPLND) during radical cystectomy (RC) in clinically lymph node-positive (cN+) bladder cancer (BCa). PATIENTS AND METHODS: In this retrospective, multicentre study we included 969 patients who underwent RC with sPLND (internal/external iliac and obturator lymph nodes) or ePLND (sPLND plus common iliac and presacral nodes) with or without platin-based peri-operative chemotherapy for cTany N1-3 M0 BCa between 1991 and 2022. We assessed the impact of ePLND on recurrence-free survival (RFS) and the distribution of recurrences (locoregional and distant recurrences). The secondary endpoint was overall survival (OS). We performed propensity-score matching using covariates associated with the extent of PLND in univariable logistic regression analysis. The association of the extent of PLND with RFS and OS was investigated using Cox regression models. RESULTS: Of 969 cN+ patients, 510 were 1:1 matched on propensity scores. The median (interquartile range [IQR]) time to recurrence was 8 (4-16) months, and median (IQR) follow-up of alive patients was 30 (13-51) months. Disease recurrence was observed in 104 patients in the ePLND and 107 in the sPLND group. Of these, 136 (27%), 47 (9.2%) and 19 patients (3.7%) experienced distant, locoregional, or both distant and locoregional disease recurrence, respectively. When stratified by the extent of PLND, we did not find a difference in recurrence patterns (P > 0.05). ePLND improved neither RFS (hazard ratio [HR] 0.91, 95% confidence interval [CI] 0.70-1.19; P = 0.5) nor OS (HR 0.78, 95% CI 0.60-1.01; P = 0.06) compared to sPLND. Stratification by induction chemotherapy did not change outcomes. CONCLUSION: Performing an ePLND at the time of RC in cN+ patients improved neither RFS nor OS compared to sPLND, regardless of induction chemotherapy status. Pretreatment risk stratification is paramount to identify ideal candidates for RC with ePLND as part of a multimodal treatment approach.
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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 | 0.001 | 0.003 |
| 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".