Eradication Therapy to Prevent Gastric Cancer in Helicobacter pylori–Positive Individuals: Systematic Review and Meta-Analysis of Randomized Controlled Trials and Observational Studies
Bibliographic record
Abstract
BACKGROUND & AIMS: Screening for, and treating, Helicobacter pylori in the general population or patients with early gastric neoplasia could reduce incidence of, and mortality from, gastric cancer. We updated a meta-analysis of randomized controlled trials (RCTs) examining this issue. METHODS: We searched the literature through October 4, 2024, identifying studies examining effect of eradication therapy on incidence of gastric cancer in H pylori-positive adults without gastric neoplasia at baseline or H pylori-positive patients with gastric neoplasia undergoing endoscopic mucosal resection (EMR) in either RCTs or observational studies. The control arm received placebo or no eradication therapy in RCTs and no eradication therapy in observational studies. Follow-up was ≥2 years. We estimated relative risks (RR) of gastric cancer incidence and mortality. RESULTS: Eleven RCTs and 13 observational studies were eligible. For RCTs, RR of gastric cancer was lower with eradication therapy in healthy H pylori-positive individuals (8 RCTs, 0.64; 95% confidence interval [CI], 0.48-0.84) and H pylori-positive patients with gastric neoplasia undergoing EMR (3 RCTs, 0.52; 95% CI, 0.38-0.71). RR of death from gastric cancer was lower with eradication therapy in healthy H pylori-positive individuals (5 RCTs, 0.78; 95% CI, 0.62-0.98). In observational studies, RR of future gastric cancer was lower with eradication therapy in H pylori-positive subjects without gastric neoplasia at baseline (11 studies, 0.56; 95% CI, 0.43-0.73) and H pylori-positive patients with gastric neoplasia undergoing EMR (2 studies, 0.19; 95% CI, 0.06-0.61). CONCLUSIONS: This meta-analysis provides further evidence that administering eradication therapy prevents gastric cancer in H pylori-positive individuals, with consistency in results among studies of different design.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.073 | 0.005 |
| Bibliometrics | 0.003 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".