Clinicopathologic Characteristics, Survival, and Treatments for Gastric Adenosquamous Carcinoma: A Population-Based Study
Bibliographic record
Abstract
Background: Gastric adenosquamous carcinoma (GASC) is a rare entity with distinctive characteristics that are not fully understood. In the present study, we evaluated the characteristics of this rare disease. Methods: The U.S. Surveillance, Epidemiology, and End Results program database was searched to determine the clinicopathologic features, prognostic factors, and treatments for 246 patients with GASC and 42,735 patients with gastric adenocarcinoma (GAC). Results: Relative to GAC, GASC is associated with higher proportions of cardia involvement, high-grade tumours, deep tumour invasion, metastatic lymph nodes, and chemotherapy treatment. In patients who underwent potentially curative surgery (PCS), GASC was associated with a higher proportion of radiotherapy use and poorer overall survival (p < 0.001), although no significant difference (p = 0.802) was observed after propensity score matching (PSM). Multivariate analysis after PSM revealed that the independent prognostic factors for GASC were TNM stage [hazard ratio (HR): 1.512; p = 0.021] and regional nodes examined (HR: 0.588; p = 0.02). In patients with advanced disease, no significant difference in survival between GASC and GAC was observed (p = 0.212), although survival was significantly poorer for GASC after PSM (p = 0.019). Multivariate analysis after PSM revealed that the independent prognostic factors for GASC were invasion depth (HR: 1.303; p = 0.036) and chemotherapy (HR: 0.444; p < 0.001). Conclusions: Relative to GAC, GASC was associated with more aggressive features, although survival outcomes were similar after PCS. Chemotherapy remains a mainstay of treatment for patients with advanced GASC, but its role remains unclear for patients who are undergoing PCS.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".