382. NUMBER OF LYMPH NODES RESECTED IS ASSOCIATED WITH OVERALL SURVIVAL IN PATHOLOGICALLY NODE-NEGATIVE ESOPHAGEAL CANCER
Bibliographic record
Abstract
Abstract Background Lymphadenectomy is a key part of curative resection of esophageal cancer, with multiple quality assurance systems suggesting a minimum of 15 lymph nodes should be resected and subjected to pathological examination. Nevertheless, whether the absolute number of nodes resected is a surrogate marker for quality in surgery and staging, or has therapeutic benefit is debated. The aim of this study was to determine the impact of lymphadenectomy on survival in patients with resected pathologically node-negative disease (both treated and untreated with neoadjuvant therapy). Methods A review of our institutional prospectively maintained database was conducted from 2010-2020 inclusive. Inclusion criteria were patients undergoing esophagectomy for esophageal cancer aged 18+ who consented to data inclusion. Exclusion criteria were patients undergoing resection for benign disease, patients with Siewert III tumours undergoing gastrectomy or extended total gastrectomy, patients undergoing re-operative surgery, or patients where final pathology was not available. Univariable and multivariable analyses were performed as appropriate. Results 195 patients (49%) had pathologically node negative disease, with median lymph node count of 25. 47% of patients were clinically node positive, but pathologically node negative following neoadjuvant therapy. On univariable survival analysis, number of nodes resected was a significant predictor of overall survival (HR 0.96, 0.93-0.98, p=0.001). On multivariable analysis, R status (HR 4.9, 1.2-21.1, p=0.03), number of nodes resected (HR 0.97, 0.94-0.99, p=0.02) and prior cN+ status (HR 2.28, 1.16-4.49, p=0.02) were predictors of overall survival. Patients with cN0, (y)pN0 disease had improved overall survival compared with cN+, (y)pN0 (median not reached vs 43.4 months, p=0.04). Conclusion Lymphadenectomy is a key part of resection of esophageal cancer. In pathologically node negative patients, the extent of lymphadenectomy remains a key predictor of overall survival. Conversion from clinically node positive to pathologically node negative disease is associated with worse outcomes compared to clinically and pathologically node negative disease. Even in early stage cancer, a thorough, multi-field lymphadenectomy should be encouraged.
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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 | 0.002 |
| 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) | 0.003 | 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".