Significant regional variation in adequacy of lymph node assessment and survival in gastric cancer
Bibliographic record
Abstract
BACKGROUND: Lymph node (LN) status is a major determinant of prognosis and treatment of gastric adenocarcinoma. The 1997 American Joint Commission on Cancer/Union Internationale Contre le Cancer guidelines were revised, requiring examination of > or =15 LN for staging. METHODS: We investigated compliance with these guidelines and the correlation with overall survival (OS) by analyzing 10,807 resected gastric cancers in the Surveillance, Epidemiology and End Results (SEER) database, 1988-2002. Kaplan-Meier survival curves were constructed; survival was compared by using Cox proportional hazards. RESULTS: Overall, 29% of cases had > or =15 LN examined. After 1997, the median number of LN assessed increased from 9 to 10 (P < .0001). Factors predictive of adequate LN assessment (ALNA) were higher stage, worse grade, age <74 years, later year of diagnosis, nonwhite race, more extensive surgery, female sex, and SEER region. Differences in the rate of ALNA between regions were noted, ranging from 19.7-53% (P < .0001). Of T1N0 patients, 19% had ALNA. Improved OS was predicted by earlier stage, lower grade, marital status, Asian race, younger age, T-stage, female sex, SEER region, and ALNA. Median OS was highest in the region with the best ALNA rate and worst in the region with the lowest (33 mos vs. 17 mos, P < .0001). Inadequate LN assessment led to poorer survival at every stage (P < .001). CONCLUSION: The overwhelming majority of patients have an inadequate LN assessment. ALNA was associated with improved OS, with significant variation across regions. Understaging due to inadequate LN assessment may affect eligibility for adjuvant therapy. Education is required to improve LN retrieval.
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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 | 0.006 |
| 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 | 0.000 |
| 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".