561. COMMONALITY AND VARIATION IN PERIOPERATIVE ESOPHAGEAL CANCER MANAGEMENT IN HIGH VOLUME EUROPEAN CENTERS
Bibliographic record
Abstract
Abstract Background Esophageal cancer is a leading cause of cancer related death worldwide. For patients with locally advanced, non-metastatic, esophageal cancer (EC), surgical resection remains an essential pillar. The multitude of surgical options have driven innovation, however, lack standardization and at times high-quality data-driven practices. A surgeon-level in-depth interview and questionnaire was created to understand the perioperative care pathways and intraoperative techniques used by high-volume European EC centres to gain insight into commonality and variation of current practice. Methods Eight (8) expert upper gastrointestinal surgeons were invited to participate in an in-depth interview and questionnaire. The focus included preoperative care pathways for esophageal adenocarcinoma of the distal esophagus/GE junction, technical aspects of esophageal resection (Ivor-Lewis) and postoperative pathways. The involvement of allied health, dedicated research programs, multidisciplinary cancer conference (MCC), follow up protocols and management of T4b EC was also assessed. Results The response rate was 100% (8/8). Majority of respondents indicated a country-level regionalization of EC care. The number of centres performing esophageal resection varied from 4 – >100. Average number of esophagectomies/year ranged from 60-150. All centres presented EC patients at MCC, had dedicated research programs, and participated in National and International EC databases. Chemoradiotherapy was the predominate neoadjuvant treatment for GEJ cancers. Pretreatment clinical staging varied, with all centres having different, but pre-defined, preoperative and postoperative pathways. Intraoperative techniques including conduit preparation, feeding tube use, pyloric intervention, thoracic duct ligation and anastomotic technique varied substantially. There was no consensus regarding follow up or management of T4b EC. Conclusion The perioperative pathways and technical aspects of esophageal resection shared some commonalities however also differed substantially across high-volume EC centres in Europe. Multicenter, pragmatic randomized controlled trials (RCTs) are needed to better delineate which techniques should be included as standard of care, and which should be abandoned.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".