Curriculum review: colorectal cancer surveillance and management of dysplasia in IBD
Bibliographic record
Abstract
The significantly increased risk of colorectal cancer (CRC) in longstanding colonic inflammatory bowel disease (IBD) justifies the need for endoscopic surveillance. Unlike sporadic CRC, IBD-related CRC does not always follow the predictable sequence of low-grade to high-grade dysplasia and finally to invasive carcinoma, probably because the genetic events shared by both diseases occur in different sequences and frequencies. Surveillance is recommended for patients who have had colonic disease for at least 8-10 years either annually, every 3 years or every 5 years with the interval dependant on the presence of additional risk factors. Currently, the recommended endoscopic strategy is high-definition chromoendoscopy with targeted biopsies, although the associated lengthier procedure time and need for experienced endoscopists has limited its uniform uptake in daily practice. There is no clear consensus on the management of dysplasia, which continues to be a challenging area particularly when endoscopically invisible. Management options include complete resection (and/or referral to a tertiary centre), close surveillance or proctocolectomy. Technical advances in endoscopic imaging such as confocal laser endomicroscopy, show exciting potential in increasing dysplasia detection rates but are still far from being routinely used in clinical practice.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".