Adult height and risk of gastric cancer: a pooled analysis within the Stomach cancer Pooling Project
Bibliographic record
Abstract
BACKGROUND: The association between height and risk of gastric cancer has been studied in several epidemiological studies with contrasting results. The aim of this study is to examine the association between adult height and gastric cancer within a large pooled analysis of case-control studies members of the Stomach cancer Pooling (StoP) Project consortium. METHODS: Data from 18 studies members of the StoP consortium were collected and analyzed. A multivariable logistic regression model was used to estimate the study-specific odds ratios (ORs) and 95% confidence intervals (CIs) for the association between 10-cm increase in height and risk of gastric cancer. Age, sex, tobacco smoking, alcohol consumption, social class, geographical area and Helicobacter pylori (H. pylori ) status were included in the regression model. Resulting estimates were then pooled with random-effect model. Analyses were conducted overall and in strata of selected variables. RESULTS: A total of 7562 cases and 19 033 controls were included in the analysis. The pooled OR was 0.96 (95% CI 0.87-1.05). A sensitivity analysis was performed restricting the results to the studies with information on H. pylori status, resulting in an OR of 0.97 (95% CI 0.79-1.20). CONCLUSION: Our study does not support a strong and consistent association between adult height and gastric cancer.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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".