Prevalence of irritable bowel syndrome and its association with colorectal cancer: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: This study evaluates the risk of colorectal cancer (CRC) in patients with Irritable Bowel Syndrome (IBS). METHODS: A literature search was performed on MEDLINE, EMBASE, SCOPUS, and Google Scholar from inception to 31st January 2020 without any limitations on article type or language for studies reporting data on CRC on patients with IBS. A meta-analysis was performed to estimate the prevalence of CRC among patients with IBS. Data extraction was according to the PRISMA guidelines. The quality of the included studies was assessed according to the Newcastle Ottawa Scale. RESULTS: Twenty-one articles were eligible for data extraction and quantitative analysis. Of them, 11 were included in the meta-analysis (IBS n = 284 366, no-IBS n = 8 390 509). The pooled prevalence of CRC in patients with IBS was 0.96% (95% CI-0.184%-2.344%). The prevalence was lowest in the constipation-predominant IBS (pooled prevalence 1.126%. Patients with IBS-D and IBS-U had an equal pooled prevalence of CRC (2.49%). Eleven studies compared the prevalence of CRC in patients with IBS with a control population. The pooled OR was 2.8 (CI 2.305-3.294). CONCLUSIONS: There was an increased risk of CRC among patients diagnosed with IBS, primarily in the first year after IBS diagnosis. REGISTRATION: The review was registered on PROSPERO (CRD42021236707).
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 | 0.011 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.030 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".