Operative link on gastritis assessment stage is an appropriate predictor of early gastric cancer
Bibliographic record
Abstract
AIM: To assess the predictive value of Operative Link on Gastritis Assessment (OLGA) and Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) stages in gastric cancer. METHODS: A prospective study was conducted with 71 patients with early gastric cancer (EGC) and 156 patients with non-EGC. All patients underwent endoscopic examination and systematic biopsy. Outcome measures were assessed and compared, including the Japanese endoscopic gastric atrophy (EGA) classification method and the modified OLGA method as well as the modified OLGIM method. Helicobacter pylori (H. pylori) status was determined for all study participants. Stepwise logistic regression modeling was performed to analyze correlations between EGC and the EGA, OLGA and OLGIM methods. RESULTS: For patients with EGC and patients with non-EGC, the proportions of moderate-to-severe EGA cases were 64.8% and 44.9%, respectively (P = 0.005), the proportions of OLGA stages III-IV cases were 52.1% and 22.4%, respectively (P < 0.001), and the proportions of OLGIM stages III-IV cases were 42.3% and 19.9%, respectively (P < 0.001). OLGA stage and OLGIM stage were significantly related to EGA classification; specifically, logistic regression modeling showed significant correlations between EGC and moderate-to-severe EGA (OR = 1.95, 95% CI: 1.06-3.58, P = 0.031) and OLGA stages III-IV (OR = 3.14, 95%CI: 1.71-5.81, P < 0.001), but no significant correlation between EGC and OLGIM stages III-IV (P = 0.781). H. pylori infection rate was significantly higher in patients with moderate-to-severe EGA (75.0% vs 54.1%, P = 0.001) or OLGA/OLGIM stages III-IV (OLGA: 83.6% vs 55.8%, P < 0.001; OLGIM: 83.6% vs 57.8%, P < 0.001). CONCLUSION: OLGA classification is optimal for EGC screening. A surveillance program including OLGA stage and H. pylori infection status may facilitate early detection of gastric cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".