Survival benefits of pelvic lymphadenectomy versus pelvic and para-aortic lymphadenectomy in patients with endometrial cancer
Bibliographic record
Abstract
BACKGROUND: Despite that pelvic and para-aortic lymphadenectomy (PPaLND) is recommended as part of accurate surgical staging by International Federation of Gynecology and Obstetrics (FIGO) in endometrial cancer, the impact of para-aortic lymphadenectomy on survival remains controversial. The aim of this work is to evaluate the survival benefits or risks in endometrial cancer patients who underwent surgical staging with or without para-aortic lymphadenectomy using meta-analysis. METHODS: Literature search was undertaken using PubMed, Embase, and Cochrane Library databases for relevant articles published between January 1, 1990, and January 1, 2017, without language restriction. The primary outcome was overall survival (OS); progression-free survival (PFS)/recurrence-free survival (RFS)/disease-free survival (DFS)/disease-related survival (DRS) was also analyzed. Subgroup analysis and sensitivity analysis were conducted to investigate the source of heterogeneity. Quality assessments were performed by Newcastle-Ottawa Quality Assessment Scale (NOS). Publication bias was evaluated by using Begg and Egger tests. The hazard ratio (HR) was pooled with random-effects or fixed-effects model as appropriate. RESULTS: Eight studies with a total of 2793 patients were included. OS was significantly longer in PPaLND group than in pelvic lymphadenectomy (PLND) group for patients with endometrial cancer [HR 0.68; 95% confidence interval (CI) 0.55-0.84, P < .001, I = 12.2%]. Subgroup analysis by recurrence risk explored the same association in patients at intermediate- or high-risk (HR 0.52; 95% CI 0.39-0.69, P < .001, I = 41.4%), but not for low-risk patients (HR 0.48; 95% CI 0.21-1.08, P = .077, I = 0). PPaLND with systematic resection of all para-aortic nodes up to renal vein also improved PFS/RFS/DFS/DRS, compared with PLND (HR 0.52, 95% CI 0.37-0.72, P < .001, I = 0). No publication bias was observed among included studies. CONCLUSION: PPaLND is associated with favorable survival outcomes in endometrial cancer patients with intermediate- or high-risk of recurrence compared with PLND, particularly with regards to OS. PPaLND with systematic resection of all para-aortic nodes up to renal vein also improve PFS compared with PLND. Further large-scale randomized clinical trials are required to validate our findings.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.023 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".