The correlation between chili pepper consumption and gastric cancer risk: A meta-analysis.
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The correlation between chili pepper intake and gastric cancer (GC) risk has been controversial. We conducted a meta-analysis of 16 studies to provide updated evidence for this uncertainty. METHODS AND STUDY DESIGN: Medline, and China National Knowledge Infrastructure (CNKI) databases were searched to obtain all qualified literature related to pepper consumption and GC incidence before June 2020. Random effects models were adopted to integrate the relative risk of individual studies. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the literature of each included study. Dose response meta-analysis was implemented through the one-stage robust error meta-regression (REMR) approach. RESULTS: 16 studies (8337 cases) were included in quantitative meta-analysis. The pooled odds ratio (OR) of GC for the highest versus the lowest category of chili consumption were 1.51 (95% confidence interval [CI]=1.02-2.00) for all countries, 2.05 (95% CI=1.15-2.95) for Mexican, 2.03 (95% CI =0.71-3.34) for Colombian, 1.92 (95% CI=1.21-2.64) for Asian and 0.48 (95% CI=0.24-0.72) for other countries. Dose-response meta-analysis showed that there was a positive linear correlation between the risk of GC and the daily frequency of chili consumption. CONCLUSIONS: Significantly increased consumption of chili pepper or capsaicin has the potential to increase the risk of gastric cancer, however, inconsistencies still exist in subgroup analysis between different regions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".