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Record W2952732266 · doi:10.1111/jgh.14759

Relationship between long‐term use of proton pump inhibitors and risk of gastric cancer: A systematic analysis

2019· review· en· W2952732266 on OpenAlexaboutno aff
Kailin Jiang, Xiaotao Jiang, Yi Wen, Liu Liao, Fengbin Liu

Bibliographic record

VenueJournal of Gastroenterology and Hepatology · 2019
Typereview
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHelicobacter pyloriCochrane LibraryCancerInternal medicineOdds ratioMeta-analysisSubgroup analysisProton-pump inhibitorGastroenterologyOncology

Abstract

fetched live from OpenAlex

BACKGROUND AND AIM: This study aims to systematically analyze the effect of long-term therapy with proton pump inhibitors (PPIs) on the risk of gastric cancer. METHODS: PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure (CNKI), and China biomedical literature database (CBM) were searched for studies before February 2019. We evaluated the quality of the included articles through the Newcastle-Ottawa Scale and gathered relevant data to calculate the pooled odds ratio (OR) through Stata14.0. RESULTS: Seven relevant articles conformed to the inclusion criteria; 943 070 patients were included. The pooled OR was 2.50; 95% CI (1.74, 3.85); the subgroup analysis results showed that patients who had used PPIs for more than 36 months were most likely to develop gastric cancer, and an increased risk was observed among patients after Helicobacter pylori eradication. Noncardia gastric cancer was more likely to develop. CONCLUSIONS: Long-term use of PPIs can possibly increase the risk of gastric cancer even among patients after H. pylori eradication; in particular, for noncardia gastric cancer, the risk increases with longer durations of PPI use. Due to the limited number of studies, more high-quality studies are required to be designed.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.357
Teacher spread0.278 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations44
Published2019
Admission routes1
Has abstractyes

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