5-Aminosalicylic Acid Is Not Protective Against Colorectal Cancer in Inflammatory Bowel Disease: A Meta-Analysis of Non-Referral Populations
Bibliographic record
Abstract
OBJECTIVES: Some studies have demonstrated that 5-aminosalicylic acid (5-ASA) is associated with a reduced risk of colorectal cancer (CRC) in inflammatory bowel disease (IBD). However, more recent population-based studies suggest no protective association. We conducted a systematic review that focused on non-referral studies to reassess the role of 5-ASA for this indication. METHODS: We searched MEDLINE, EMBASE, and the Cochrane databases for studies of non-referral populations that assessed the association between 5-ASA use for at least 1 year and colorectal neoplasia between 1966 and 2011 and conducted a quantitative meta-analysis. RESULTS: Four observational studies fulfilled inclusion criteria. The pooled adjusted odds ratio (aOR) was 0.95 (95% confidence interval (CI): 0.66-1.38), but there was moderate heterogeneity (I2 = 58.2%; P = 0.07). A sensitivity analysis that included a fifth study in which 5-ASA use was only for a minimum of 3 months yielded a pooled aOR of 0.82 (95% CI: 0.54-1.26). A series of sensitivity analyses in which each of the four studies was excluded one at a time did not show any significant change in the overall pooled OR. We conducted a separate meta-analysis of nine clinic-based studies, which, in contrast, yielded a pooled OR of 0.58 (95% CI: 0.45-0.75). CONCLUSIONS: Our meta-analysis yielded inconsistent results that were dependent on the inclusion of either non-referral or clinic-based populations. Based on non-referral studies, there does not seem to be a protective effect of 5-ASA on CRC in IBD. However, heterogeneity among these studies limits their interpretation.
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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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.061 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".