High Adherence to Surveillance Guidelines in Inflammatory Bowel Disease Patients Results in Low Colorectal Cancer and Dysplasia Rates, While Rates of Dysplasia are Low Before the Suggested Onset of Surveillance
Bibliographic record
Abstract
BACKGROUND: Patients with Crohn's disease [CD] and ulcerative colitis [UC] are at increased risk for colorectal dysplasia [CRD] and colorectal cancer [CRC]. Adherence to CRC surveillance guidelines is reportedly low internationally. AIM: To evaluate surveillance practices at the tertiary IBD Center of the McGill University Health Center [MUHC] and to determine CRD/CRC incidence. METHODS: A representative inflammatory bowel disease cohort with at least 8 years of disease duration [or with primary sclerosing cholangitis] who visited the MUHC between July 1 and December 31, 2016 were included. Adherence to surveillance guidelines was compared to modified 2010 British Society of Gastroenterology guidelines. Incidence rates of CRC, high-grade dysplasia [HGD], low-grade dysplasia [LGD] and colorectal adenomas [CRA] were calculated based on pathology. RESULTS: In total, 1356 CD and UC patients (disease duration: 12 [interquartile range: 6-22) and 10 [interquartile range: 5-19] years) were identified. The surveillance cohort consisted of 680 patients [296 UC and 384 CD]. Adherence to surveillance guidelines was 76/82% in UC/colonic CD. An adequate number of biopsies were taken in 54/54% of UC/colonic CD patients. The incidence of CRC/HGD in UC and CD with colonic involvement was 19.5/58.5 and 25.1/37.6 per 100,000 patient-years, respectively. The incidence of dysplasia before 8 years of disease duration was low in both UC/CD [19.5 and 12.5/100,000 patient-years] with no CRC detected. The CRA rate was 30/38% in UC/colonic CD. CONCLUSION: High adherence to surveillance guidelines and low CRC and dysplasia, but not CRA rates were found, suggesting that adhering to updated, stratified, surveillance recommendations may result in low advanced neoplasia rates. The incidence of dysplasia before the start of surveillance was low.
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 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) | 0.000 | 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".