Colorectal Cancer in Ulcerative Colitis: Mechanisms, Surveillance and Chemoprevention
Bibliographic record
Abstract
Patients with ulcerative colitis (UC) are at a two- to three-fold increased risk of developing colorectal cancer (CRC) than the general population based on population-based data. UC-CRC has generated a series of clinical problems, which are reflected in its worse prognosis and higher mortality than sporadic CRC. Chronic inflammation is a significant contributor to the development of UC-CRC, so comprehending the relationship between the proinflammatory factors and epithelial cells together with downstream signaling pathways is the core to elucidate the mechanisms involved in developing of CRC. Clinical studies have shown the importance of early prevention, detection and management of CRC in patients with UC, and colonoscopic surveillance at regular intervals with multiple biopsies is considered the most effective way. The use of endoscopy with targeted biopsies of visible lesions has been supported in most populations. In contrast, random biopsies in patients with high-risk characteristics have been suggested during surveillance. Some of the agents used to treat UC are chemopreventive, the effects of which will be examined in cancers in UC in a population-based setting. In this review, we outline the current state of potential risk factors and chemopreventive recommendations in UC-CRC, with a specific focus on the proinflammatory mechanisms in promoting CRC and evidence for personalized surveillance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".