Does The Use of 5-Aminosalicylates in Inflammatory Bowel Disease Prevent The Development of Colorectal Cancer?
Bibliographic record
Abstract
OBJECTIVES: There is increased interest in determining whether 5-aminosalicylate (5-ASA) use can prevent the development of colorectal cancer (CRC) among patients with inflammatory bowel disease (IBD). The aim of this study was to determine whether use of 5-ASA was associated with a reduced risk of CRC in these patients. METHODS: We extracted from our population-based University of Manitoba Inflammatory Bowel Disease Epidemiology Database the number of patients with a new diagnosis of CRC between the years 1997 and 2000. From within our Inflammatory Bowel Disease Epidemiology Database we extracted a control group of IBD patients who did not develop CRC matched to the case group who did develop CRC by age, sex, diagnosis, year of diagnosis, and geographic area of residence. We linked cases and controls with Manitoba Health's Drug Program Information Network to study 5-ASA use within 2 yr before CRC diagnosis. The Drug Program Information Network database is a population-based database that was established in 1995 and that records all prescription drugs. RESULTS: There were 25 cases of IBD identified as having CRC. These were matched with 348 cases of IBD who did not develop CRC. CRC cases were more likely to be exposed to 5-ASA (odds ratio = 1.46; 95% CI = 0.58-3.73) but this result was not statistically significant. The mean total days of use was 400.9 days +/- 185.9 among CRC cases versus 420.2 days +/- 241.7 among non-CRC cases (p = 0.92). The prescribed daily dose was 2295 mg/day +/- 1041 mg among CRC cases and 1811 mg +/- 520 mg among controls (p = 0.21). CONCLUSIONS: These data do not support 5-ASA as protective in preventing 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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".