5-Aminosalicylate Is Not Chemoprophylactic for Colorectal Cancer in IBD: A Population Based Study
Bibliographic record
Abstract
OBJECTIVES: We aimed to determine if use of 5-aminosalicylates (5-ASA) was associated with a reduced risk of colorectal cancer (CRC) in people with inflammatory bowel disease (IBD). METHODS: We used the population-based University of Manitoba IBD Epidemiology Database that tracks all health-care visits from 1984 to 2008 of all Manitobans with IBD and all prescription medication use since 1995. In 2008, there were 8,744 subjects with IBD (ulcerative colitis 4,325, Crohn's disease 4,419, females 4,851, males 3,893). In study I, we assessed the incidence of CRC among 5-ASA users (≥1 year, ≥5 years of cumulative use) compared with nonusers. In study II, we assessed a cohort of those with CRC (n=101) diagnosed in 1995-2008, matched to a control cohort by age, sex, disease duration, and disease diagnosis without CRC (n=303), and logistic analysis was undertaken. RESULTS: For study I, the hazard ratio for CRC among 5-ASA users was 1.04 (95% confidence interval (CI) 0.67-1.62, P=0.87) at ≥1 year of use and 2.01 (95% CI 1.04-3.9, P=0.038) at ≥ 5 years of use with no difference when assessing by diagnosis. Males, but not females, using 5-ASA for ≥ 5 years had an increased risk of CRC. In study II, CRC cases had similar use of any 5-ASA compared with controls for ≥ 1 year of use (1.02, 95% CI 0.60-1.74) or ≥ 5 years (1.96, 95% CI 0.84-4.55), and a similar mean number of 5-ASA prescriptions at 10 vs. 11 (P=0.8) and a similar mean number of dose days at 330 vs. 410 (P=0.69). CONCLUSIONS: Our results support the majority of studies to date that 5-ASA is not chemoprophylactic in IBD for CRC.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".