78 Interhospital Variations in Practice and Outcomes for Endoscopic Resection of Early Esophago-Gastric Adenocarcinoma: Multi-Center CONGRESS Dataset Analysis
Bibliographic record
Abstract
Abstract Aim This study aimed to evaluate inter-hospital variation in practice and clinical outcomes following endoscopic resection (ER) for early-stage (T1N0) oesophago-gastric (OG) adenocarcinoma using a large multi-centre dataset. ER offers organ-preserving, potentially curative treatment but is a complex procedure performed in specialised centres. Centre volumes for ER vary significantly, yet the clinical implications of such variability remain unclear. Method A retrospective analysis was conducted using the CONGRESS database, a UK-centric multi-centre registry of patients treated for T1N0 OG cancer between 2015–2022. Demographics, tumour characteristics, and outcomes—including R1 resection, procedural complications, and progression to surgery— for patients undergoing ER were analysed. Patients were stratified into tertiles by hospital ER volume, and outcomes between high- and low-volume centres were compared. Multivariable logistic regression assessed the association between centre volume and clinical outcomes. Results 1215 patients from 28 centres were included. ER volume per centre for OG cancer ranged from 2–154 over the 7-year period. R1 resection rates ranged from 0-67%, complication rates ranged from 0-50%. High-volume centres had lower R1 resection (17.3% vs. 26.4%, p=0.001), complication rates (3.8% vs. 8.2%, p=0.007) and progression to surgery rates (9.8% vs 20.7%, p<0.001), compared to low-volume centres. These differences remained after adjustment for patient and tumour variables, with low-volume centres showing higher odds of R1 resection (OR 0.63, p=0.022), procedural complications (OR 0.41, p=0.007), and rates of subsequent surgery (OR 0.38, p<0.001). Conclusions This study demonstrates large variations in clinical outcomes for ER in OG cancer, with a significant association between centre volume and clinical outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".