Association between <i>Helicobacter pylori</i> infection and tumor markers: an observational retrospective study
Bibliographic record
Abstract
Objective Helicobacter pylori infection is a major cause of several cancers such as gastric, pancreatic and lung. The relationship between H. pylori and tumour markers continues to remain unclear. The primary goal of this study is to clarify the associations between H. pylori infection and six tumour markers (ie, carcinoembryonic antigen (CEA), cancer antigen (CA) 153, CA199, CA724, CA125 and alpha-fetoprotein (AFP)). The secondary goal is to provide understanding for further research about H. pylori infection and gastrointestinal cancer. Design Observational retrospective study. Setting The study was performed in Beijing, China, where enrolled subjects had all passed health examinations during the period of 2012–2016. Subjects were categorised into H. pylori (+) and H. pylori (–) group according to their infection status and the measured six biomarkers. We used logistic regression models and generalised linear models to explore the associations between H. pylori infection and six tumour markers (ie, CEA, CA153, CA199, CA724, CA125 and AFP). Participants A total of 14 689 subjects were included and 6493 (44.2%) subjects were infected by H. pylori . The subjects had a mean age (1SD) of 45 (18) years. There were 4530 (31.0%) female subjects. Results After adjusting for the confounding factors, infections with H. pylori were found to be significantly associated with abnormal ratios in CEA, AFP and CA724 of H. pylori (+) to H. pylori (–) groups. Significant positive correlation was found between H. pylori infection and CEA values (adjusted β = 0.056; 95% CI 0.005 to 0.107; p=0.033). Conclusions In this observational retrospective study, we observed the H. pylori infections in a Chinese population and found higher CEA level in H. pylori -infected subjects and abnormal ratios in CEA, AFP and CA724 in infected subjects to uninfected subjects. These findings may provide a basis for future exploration with H. pylori and tumour markers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".