Cigarette smoking and gastric cancer in the Stomach Cancer Pooling (StoP) Project
Bibliographic record
Abstract
Tobacco smoking is a known cause of gastric cancer, but several aspects of the association remain imprecisely quantified. We examined the relation between cigarette smoking and the risk of gastric cancer using a uniquely large dataset of 23 epidemiological studies within the 'Stomach cancer Pooling (StoP) Project', including 10 290 cases and 26 145 controls. We estimated summary odds ratios (ORs) and the corresponding 95% confidence intervals (CIs) by pooling study-specific ORs using random-effects models. Compared with never smokers, the ORs were 1.20 (95% CI: 1.09-1.32) for ever, 1.12 (95% CI: 0.99-1.27) for former, and 1.25 (95% CI: 1.11-1.40) for current cigarette smokers. Among current smokers, the risk increased with number of cigarettes per day to reach an OR of 1.32 (95% CI: 1.10-1.58) for smokers of more than 20 cigarettes per day. The risk increased with duration of smoking, to reach an OR of 1.33 (95% CI: 1.14-1.54) for more than 40 years of smoking and decreased with increasing time since stopping cigarette smoking (P for trend<0.01) and became similar to that of never smokers 10 years after stopping. Risks were somewhat higher for cardia than noncardia gastric cancer. Risks were similar when considering only studies with information on Helicobacter pylori infection and comparing all cases to H. pylori+ controls only. This study provides the most precise estimate of the detrimental effect of cigarette smoking on the risk of gastric cancer on the basis of individual data, including the relationship with dose and duration, and the decrease in risk following stopping smoking.
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 | 0.021 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".