Is the Glasgow Prognostic Score Applicable to Both Early- and Advanced-Stage Gastric Cancers?
Bibliographic record
Abstract
BACKGROUND: The Glasgow prognostic score (GPS) has been reported as a sensitive prognostic marker for gastric cancer. This study aimed to investigate whether the GPS is equally applicable to patients with early-stage and advanced-stage gastric cancers. METHODS: Patients (n = 544) who underwent elective gastrectomy for gastric cancer between 2007 and 2015 were retrospectively studied. GPSs of 2, 1, and 0 were allocated to patients with both an elevated C-reactive protein level (> 1.0 mg/dL) and hypoalbuminemia (< 3.5 mg/dL), patients with only one of these abnormalities, and patients with neither abnormality, respectively. The prognostic factors relevant to patients with early-stage (pStage I, n = 304) and advanced-stage (pStage II, III, and IV, n = 240) gastric cancer were analyzed through univariate and multivariate analyses. RESULTS: In the early-stage group, only the serum carbohydrate antigen (CA) 19-9 level (P = 0.037) was a significant prognostic factor in the multivariate analysis; the GPS was not significant (P = 0.095). In the advanced-stage group, an American Society of Anesthesiologists physical status of 3 or 4 (P = 0.032), elevated carcinoembryonic antigen (CEA) (P = 0.043) and CA19-9 (P = 0.045) levels, a GPS 1 - 2 (P = 0.017), and type 4 tumor (P = 0.020) correlated significantly with worse overall survival. CONCLUSIONS: GPS is a simple and useful prognostic score for patients with advanced-stage, but is not applicable to early-stage patients.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".