Palliative Gastrectomy Improves the Survival of Patients with Metastatic Early-Onset Gastric Cancer: A Retrospective Cohort Study
Bibliographic record
Abstract
Background: Recent studies have found that patients with incurable gastric cancer might benefit from palliative gastrectomy, but the impact of palliative gastrectomy on metastatic early-onset gastric cancer (mEOGC) patients remains unclear. Methods: We analyzed mEOGC patients enrolled in the Surveillance, Epidemiology, and End Results registry from January 2004 to December 2018. Propensity score matching (PSM) analysis with 1:1 matching and the nearest-neighbor matching method were used to ensure well-balanced characteristics between the groups of patients with palliative gastrectomy and those without surgery. Kaplan–Meier survival analysis and Cox proportional hazards regression models were used to evaluate the overall survival (OS) and cause-specific survival (CSS) risk with corresponding 95% confidence intervals (CIs). Results: Of 3641 mEOGC patients, 442 (12.1%) received palliative gastrectomy. After PSM, 596 patients were included in the analysis, with 298 in each group. For the matched cohort, the median survival was 8 months, and the 5-year survival was 4.0%. The median OS of mEOGC patients undergoing palliative gastrectomy was significantly longer than that of patients without surgery (13 months vs. 6 months, p < 0.001), and palliative gastrectomy remained an independent protective factor after adjusting for confounders (HR 0.459, 95% CI 0.382–0.552, p < 0.001), and the protective effect was robust in the subgroup analysis. Similar results were indicated in CSS. Stratified analyses by treatment modality also warranted the superiority of palliative-gastrectomy-based treatment in improving OS and CSS. Conclusions: mEOGC patients with palliative gastrectomy had a significantly longer survival time than patients without surgery. Exploratory analysis confirmed that surgery-based therapy modality was superior in improving survival time.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".