Fish consumption and gastric cancer within the Stomach cancer Pooling (StoP) Project
Bibliographic record
Abstract
Gastric cancer is among the most common cancer and cause of cancer death. We conducted a meta-analysis of 25 case-control studies from the Stomach cancer Pooling Project to assess the association between fish or canned fish consumption and the risk of gastric cancer. 10,431 cases and 24,903 controls were available. We found no association between fish consumption and risk of gastric cancer (pooled odds ratios (OR) = 0.99; 95% confidence interval (CI) 0.86-1.13, for at least one serving/week vs none). Geographical differences were found: in Asia an increased intake of fish was associated with a lower stomach cancer risk. In the sensitivity analyses, fish consumption was associated to a lower risk of gastric cancer in models adjusted for family history of gastric cancer (OR = 0.80, 95% CI 0.72-0.89) and Helicobacter Pylori infection (OR = 0.72, 95% CI 0.60-0.88), but not for body mass index or energy intake. Seven studies collected information on canned fish (4525 cases and 8073 controls). No association was found for canned fish (OR = 0.96, 95% CI 0.82-1.13). In conclusion, our results provide evidence that fish and canned fish intake are not associated with gastric cancer risk, although geographical differences have been highlighted, with a lower risk of gastric cancer in Asia.
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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 | 0.019 | 0.032 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.020 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".