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Record W3012615718 · doi:10.1136/gutjnl-2020-320839

<i>Helicobacter pylori</i>eradication therapy to prevent gastric cancer: systematic review and meta-analysis

2020· review· en· W3012615718 on OpenAlexaff
Alexander C. Ford, Yuhong Yuan, Paul Moayyedi

Bibliographic record

VenueGut · 2020
Typereview
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsMcMaster University Medical Centre
Fundersnot available
KeywordsMedicineHelicobacter pyloriMeta-analysisInternal medicineNumber needed to treatCancerGastroenterologyRelative riskPlaceboIncidence (geometry)Randomized controlled trialPopulationConfidence intervalPathologyAlternative medicine

Abstract

fetched live from OpenAlex

Objectives Gastric cancer is strongly associated withHelicobacter pylori(H. pylori). We conducted a previous systematic review and meta-analysis that suggested eradication therapy reduced future incidence of gastric cancer, but effect size was uncertain, and there was no reduction in gastric cancer-related mortality. We updated this meta-analysis, as more data has accumulated. We also evaluated impact of eradication therapy on future risk of gastric cancer in patients having endoscopic mucosal resection for gastric neoplasia. Design We searched the medical literature through February 2020 to identify randomised controlled trials (RCTs) examining effect of eradication therapy on subsequent occurrence of gastric cancer in healthyH. pylori-positive adults, and inH. pylori-positive patients with gastric neoplasia undergoing endoscopic mucosal resection. The control arm received placebo or no treatment. Follow-up was for ≥2 years. We estimated the relative risk (RR) number needed to treat (NNT), and evaluated the disability-adjusted life-years (DALYs) gained from screening from the meta-analysis. Results We identified 10 RCTs, seven recruited 8323 healthy individuals, and three randomised 1841 patients with gastric neoplasia. In healthy individuals, eradication therapy reduced incidence of gastric cancer (RR=0.54; 95% CI 0.40 to 0.72, NNT=72), and reduced mortality from gastric cancer (RR=0.61; 95% CI 0.40 to 0.92, NNT=135), but did not affect all-cause mortality. These data suggest that 8 743 815 DALYs (95% CI 5 646 173 to 11 847 456) would be gained if population screening and treatment was implemented globally. In patients with gastric neoplasia, eradication therapy also reduced incidence of future gastric cancer (RR=0.49; 95% CI 0.34 to 0.70, NNT=21). Adverse events were incompletely reported. Conclusion There is moderate evidence to suggest thatH. pylorieradication therapy reduces the incidence of gastric cancer in healthy individuals and patients with gastric neoplasia in East Asian countries. There also appears to be a reduction in gastric cancer-related mortality.

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 imitation

Not 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.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.071

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.036
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0150.026
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.083
GPT teacher head0.357
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations438
Published2020
Admission routes1
Has abstractyes

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