Exposure to Ranitidine and Risk of Bladder Cancer: A Nested Case-Control Study
Bibliographic record
Abstract
INTRODUCTION: Ranitidine has been shown to contain the carcinogen N-nitrosodimethylamine and increase urinary N-nitrosodimethylamine in humans. We investigated whether ranitidine use is associated with increased bladder cancer risk. METHODS: A nested case-control study was conducted within the Primary Care Clinical Informatics Unit Research database which contains general practice records from Scotland. Bladder cancer cases, diagnosed between 1999 and 2011, were identified and matched with up to 5 controls (based on age, sex, general practice, and date of registration). Ranitidine, other histamine-2 receptor agonists, and proton pump inhibitors were identified from prescribing records. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using conditional logistic regression after adjusting for comorbidities and smoking. RESULTS: There were 3,260 cases and 14,037 controls. There was evidence of an increased risk of bladder cancer in ranitidine users, compared with nonusers (fully adjusted OR = 1.22; 95% CI 1.06-1.40), which was more marked with use for over 3 years of ranitidine (fully adjusted OR = 1.43; 95% CI 1.05-1.94). By contrast, there was little evidence of any association between proton pump inhibitor use and bladder cancer risk based on any use (fully adjusted OR = 0.98; 95% CI 0.88-1.11) or over 3 years of use (fully adjusted OR = 0.98; 95% CI 0.80-1.20). DISCUSSION: In this large population-based study, the use of ranitidine particularly long-term use was associated with an increased risk of bladder cancer. Further studies are necessary to attempt to replicate this finding in other settings.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".