Nonsteroidal Anti-inflammatory Drugs and the Esophageal Inflammation-Metaplasia-Adenocarcinoma Sequence
Bibliographic record
Abstract
Observational studies suggest that nonsteroidal anti-inflammatory drugs (NSAIDs) reduce the risk of esophageal adenocarcinoma, but it is not known at what stage they may act in the esophageal inflammation-metaplasia-adenocarcinoma sequence. In an all-Ireland case-control study, we investigated the relationship between the use of NSAIDs and risk of reflux esophagitis, Barrett's esophagus, and esophageal adenocarcinoma. Patients with esophageal adenocarcinoma, long-segment Barrett's esophagus and population controls were recruited from throughout Ireland. Esophagitis patients were recruited from Northern Ireland only. Data were collected on known and potential risk factors for esophageal adenocarcinoma and on the use of NSAIDs, including aspirin, at least 1 year before interview. Associations between use of NSAIDs and the stages of the esophageal inflammation-metaplasia-adenocarcinoma sequence were estimated by multiple logistic regression. In total, 230 reflux esophagitis, 224 Barrett's esophagus, and 227 esophageal adenocarcinoma and 260 population controls were recruited. Use of aspirin and NSAIDs was associated with a reduced risk of Barrett's esophagus [odds ratio [OR; 95% confidence interval (95% CI)], 0.53 (0.31-0.90) and 0.40 (0.19-0.81), respectively] and esophageal adenocarcinoma [OR (95% CI), 0.57 (0.36-0.93) and 0.58 (0.31-1.08), respectively]. Barrett's esophagus and esophageal adenocarcinoma patients were less likely than controls to have used NSAIDs. Selection or recall bias may explain these results and the results of previous observational studies indicating a protective effect of NSAIDs against esophageal adenocarcinoma. If NSAIDs have a true protective effect on the esophageal inflammation-metaplasia-adenocarcinoma sequence, they may act early in the sequence.
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 | 0.002 | 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 | 0.001 | 0.002 |
| 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".