Extended vs. Standard Pelvic Lymph Node Dissection in Bladder Cancer Patients Undergoing Radical Cystectomy: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background/Objectives: Pelvic lymph node dissection during radical cystectomy has been established to be important for staging and therapeutic purposes. However, there is uncertainty regarding the optimal extent of nodal dissection. This study aimed to assess the impact of an extended pelvic lymphadenectomy template compared to a standard template in patients with bladder cancer undergoing radical cystectomy. Methods: We performed a systematic review and meta-analysis of randomised studies comparing extended pelvic lymph node dissection to standard pelvic lymph node dissection in patients undergoing radical cystectomy. A search of multiple databases was performed up to October 2024. The standard template was defined as including at least the obturator and internal and external iliac nodes. An extended template was defined as a standard template plus the removal of proximal nodal packets. The primary outcomes were overall survival and major Clavien–Dindo complications. Results: Two studies encompassing a total of 933 participants met the eligibility criteria. There was no observed improvement in overall survival with extended lymph node dissection compared to limited dissection [HR 0.95, 95%CI 0.66–1.4]. In addition, extended lymph node dissection was associated with an increased risk of grade ≥3 Clavien–Dindo complications compared to limited nodal dissection [RR 1.2, 95%CI 1.02–1.37]. There was also an increased risk of lymphoceles requiring intervention with extended lymphadenectomy. Conclusions: Extended pelvic lymphadenectomy does not improve oncological outcomes and is associated with increased morbidity compared to a standard template in bladder cancer patients undergoing radical cystectomy.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".