Prognostic Relevance of Weight and Weight Loss during Multimodal Therapy for Oesophagogastric Tumours
Bibliographic record
Abstract
The prognostic meaning of weight loss (WL) during standard treatment for operable oesophagogastric cancer is still unclear. The aim of this study is to analyse the prognostic effect of WL during perioperative chemotherapy (PC) for gastric cancer (GC) and oesophageal adenocarcinomas (OAC). We retrospectively analysed data from 128 patients (pts) with GC and OAC who underwent surgery in the context of multimodal treatment with PC. We collected data on WL during different steps of therapy together with other histopathologic and demographic information. We analysed the effects on overall survival (OS) and disease-free survival (DFS). Results: Pts with WL ≥ 5% during neoadjuvant chemotherapy exhibited significantly worse OS compared with pts with WL < 5% (median OS: 23.6 months [95% CI: 4.4−42.9] vs. 63.5 months [95% CI: 50.7−76.2], p = 0.007) and DFS (median DFS: 12.5 months [95% CI: 2.9−22.1] vs. 63.5 months [95% CI: 31.6−95.4], p = 0.016). Pts with WL ≥ 14% during the whole treatment exhibited significantly worse OS compared with pts with WL < 14% (median OS: 43.7 months [95% CI: 13.2−74.2] vs. not reached, p = 0.028) and DFS (median DFS: 34.3 months [95% CI: 14.0−54.5] vs. not reached, p = 0.038). Conclusion: WL patterns during neoadjuvant chemotherapy and during the whole treatment correlate with a significantly worse prognosis in operated pts with curative GC or OAC in the context of a multimodal treatment with PC. A validation of this prognostic effect in prospective studies is warranted.
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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 | 0.000 | 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) | 0.000 | 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 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".