Impact of bulky loco-regional lymphadenopathy in esophageal adenocarcinoma on survival: a retrospective single center analysis
Bibliographic record
Abstract
The relationship between 'bulky' locoregional lymphadenopathy and survival has not been investigated in the setting of esophageal adenocarcinoma (EAC). This study aimed to explore whether bulky regional lymphadenopathy at diagnosis affected survival outcomes in patients with EAC treated with neoadjuvant chemotherapy and en bloc resection. A single-center retrospective review of a prospectively maintained upper GI cancer surgical database was performed between January 2012 and December 2019. Patients with locally advanced EAC (cT2-3, N+, M0) treated with neoadjuvant docetaxel-based chemotherapy and transthoracic en bloc esophagogastrectomy were identified. Computed tomography scans from before the initiation of treatment were reviewed, and patients were stratified according to whether bulky loco-regional lymph nodes were present. This was defined as lymphadenopathy >2 cm in any axis. Overall survival was compared, and a Cox multivariate regression model was calculated. Two hundred twenty-five of the eight hundred seventy patients identified met the inclusion criteria. Forty-eight (21%) had bulky lymphadenopathy, leaving 177 allocated to the control group. More patients with bulky lymphadenopathy had ypN3 disease (18/48, 38% vs. 39/177, 20%, P = 0.025). Among patients with bulky lymphadenopathy, overall survival was generally worse (32.6 vs. 59.1 months, P = 0.012). However, among the 9/48 (19%) patients with bulky lymphadenopathy who achieved ypN- status survival outcomes were similar to those with non-bulky lymphadenopathy who also achieved lymph node sterilization. Poor differentiation (HR 1.8, 95% CI 1.0-2.9, P = 0.034), ypN+ (HR 1.9, 95% CI 1.1-3.6, P = 0.032), and bulky lymphadenopathy were independently associated with an increased risk of death (HR 1.7, 1.0-2.9, P = 0.048). Bulky regional lymphadenopathy is associated with a poor prognosis. Efforts to identify the ideal treatment regimen for these patients are urgently required.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".