Textbook Outcome and Survival in Patients With Gastric Cancer
Bibliographic record
Abstract
Objective: To examine the association between Textbook Outcome (TO)—a new composite quality measurement—and long-term survival in gastric cancer surgery. Background: Single-quality indicators do not sufficiently reflect the complex and multifaceted nature of perioperative care in patients with gastric adenocarcinoma. Methods: All patients undergoing gastrectomy for nonmetastatic gastric adenocarcinoma registered in the Population Registry of Esophageal and Stomach Tumours of Ontario (PRESTO) between 2004 and 2015 were included. TO was defined according to negative margins; >15 lymph nodes sampled; no severe complications; no re-interventions; no unplanned ICU admission; length of stay ≤21 days; no 30-day readmission; and no 30-day mortality. Three-year survival was estimated using the Kaplan-Meier method. A marginal multivariable Cox proportional-hazards model was used to estimate the association between achieving TO metrics and long-term survival. E-value methodology was used to assess for risk of residual confounding. Results: Of the 1836 patients included in this study, 402 (22%) achieved all TO metrics. TO patients had a higher 3-year survival rate compared to non-TO patients (75% vs 55%, log-rank P < 0.001). After adjustments for covariates and clustering within hospitals, TO was associated with a 41% reduction in mortality (adjusted hazards ratio 0.59, 95% confidence interval 0.48, 0.72, P < 0.001). These results were robust to potential residual confounding. Conclusions: Achieving TO is strongly associated with improved long-term survival in gastric cancer patients and merits further focus in surgical quality improvement efforts.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".