Gastroesophageal Reflux in Relation to Adenocarcinomas of the Esophagus: A Pooled Analysis from the Barrett’s and Esophageal Adenocarcinoma Consortium (BEACON)
Bibliographic record
Abstract
BACKGROUND: Previous studies have evidenced an association between gastroesophageal reflux and esophageal adenocarcinoma (EA). It is unknown to what extent these associations vary by population, age, sex, body mass index, and cigarette smoking, or whether duration and frequency of symptoms interact in predicting risk. The Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) allowed an in-depth assessment of these issues. METHODS: Detailed information on heartburn and regurgitation symptoms and covariates were available from five BEACON case-control studies of EA and esophagogastric junction adenocarcinoma (EGJA). We conducted single-study multivariable logistic regressions followed by random-effects meta-analysis. Stratified analyses, meta-regressions, and sensitivity analyses were also conducted. RESULTS: Five studies provided 1,128 EA cases, 1,229 EGJA cases, and 4,057 controls for analysis. All summary estimates indicated positive, significant associations between heartburn/regurgitation symptoms and EA. Increasing heartburn duration was associated with increasing EA risk; odds ratios were 2.80, 3.85, and 6.24 for symptom durations of <10 years, 10 to <20 years, and ≥20 years. Associations with EGJA were slighter weaker, but still statistically significant for those with the highest exposure. Both frequency and duration of heartburn/regurgitation symptoms were independently associated with higher risk. We observed similar strengths of associations when stratified by age, sex, cigarette smoking, and body mass index. CONCLUSIONS: This analysis indicates that the association between heartburn/regurgitation symptoms and EA is strong, increases with increased duration and/or frequency, and is consistent across major risk factors. Weaker associations for EGJA suggest that this cancer site has a dissimilar pathogenesis or represents a mixed population of patients.
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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 | 0.020 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.043 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".