<scp>GERD</scp> and Upper Aerodigestive Tract Cancer Risk: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
OBJECTIVE: Gastroesophageal reflux disease (GERD) is highly prevalent, yet its association with upper aerodigestive tract (UADT) cancers beyond esophageal adenocarcinoma remains incompletely defined. This systematic review and meta-analysis aimed to quantify the risk of specific UADT cancers in individuals with GERD. DATA SOURCES: A comprehensive search of PubMed, Embase, Scopus, the Cochrane Library, and CINAHL was conducted for studies published from January 2000 to October 2024. REVIEW METHODS: Observational studies (cohort or case-control) evaluating GERD as a risk factor for UADT cancers in adults were included, following PRISMA guidelines (PROSPERO: CRD42024602545). Esophageal adenocarcinoma was excluded due to its well-established association with GERD. Study quality was assessed using the Newcastle-Ottawa scale. Pooled relative risks (RR) and 95% confidence intervals (CI) were calculated using random effects models. RESULTS: Seventeen studies (12 case-control, 5 cohort), encompassing 1,768,394 participants, met inclusion criteria. GERD was significantly associated with laryngeal cancer (RR = 1.65, 95% CI = 1.19-2.31). No significant associations were found for pharyngeal, oropharyngeal, hypopharyngeal, or esophageal squamous cell carcinoma. Subgroup analysis showed stronger associations in U.S.-based studies (RR = 1.61) and in studies using ICD-coded GERD (RR = 1.93). CONCLUSION: GERD is associated with an increased risk of laryngeal cancer. Findings support further investigation into reflux-related carcinogenesis in the UADT, particularly in high-risk populations.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".