Siewert II esophagogastric junction adenocarcinoma: Still searching for the right treatment transabdominal or transthoracic surgical approaches?
Bibliographic record
Abstract
INTRODUCTION: To date, the discussion is still ongoing whether the Siewert II adenocarcinoma of the esophagogastric junction (AEG) should be resected either by thoracoabdominal esophagectomy or gastrectomy with resection of the distal esophagus by transhiatal extension. The aim of our study was to compare the oncological and perioperative outcomes of the transthoracic approach (TTA) and the transabdominal approach (TAA). METHODS: Searches of electronic databases identifying studies from Cochrane, PubMed and Google Scholar were performed. Randomised and non-randomised studies comparing TTA and TAA approaches for surgical treatment of AEG Siewert type II were included. The Newcastle-Ottawa and Jada scales were used to evaluate methodological quality. The risk of bias was assessed using the Rob v2 and Robins-I tools. Meta-analyses were conducted for the outcomes. RESULTS: We included 17 trials (2 randomised controlled trials and 15 cohorts) involving 15297 patients. Longer three-year overall survival, five-year overall survival and R0 resection rates were observed in the TTA group. However, TTA had greater morbidity and pulmonary complications. CONCLUSION: Transthoracic approach appears to be preferable for selected Siewert II tumours. This may lead to higher survival rates and better R0 resection rate. Well-designed studies are needed to confirm the results of this systematic review.
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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 | 0.008 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".