High Risk of Colorectal Cancer After High‐Grade Dysplasia in Inflammatory Bowel Disease Patients
Bibliographic record
Abstract
BACKGROUND: There are limited data on colorectal cancer (CRC) risk after high-grade dysplasia in inflammatory bowel disease. AIMS: To determine the long-term CRC and neoplasia risk after a first diagnosis of high-grade dysplasia in inflammatory bowel disease, and to assess utilisation of high-grade dysplasia treatment strategies over the past three decades. METHODS: In this nationwide retrospective cohort study, patients with colonic inflammatory bowel disease and high-grade dysplasia diagnosis between 1991 and 2021 were extracted from the Dutch nationwide pathology databank (PALGA). The primary outcome was the cumulative incidence of metachronous CRC. Kaplan-Meier curves were used to show proctocolectomy-free survival per decade. RESULTS: CRC was diagnosed in 348 of 1220 patients (28.5%). Of these, 204 (16.7%) were diagnosed with CRC within 6 months after the first high-grade dysplasia diagnosis and were considered synchronous patients. Metachronous CRC was diagnosed in 144 of 1016 patients (14.2%) after a median of 3.6 years. The 1-, 5- and 10-year cumulative incidences of metachronous CRC after high-grade dysplasia were 2.9%, 9.9% and 15.5%, respectively. The 1-, 5- and 10-year cumulative incidences of metachronous neoplasia were 18.3%, 51.2% and 68.0%, respectively. Proctocolectomy-free survival after high-grade dysplasia decreased over time. CONCLUSIONS: The risk of synchronous and metachronous CRC after a diagnosis of high-grade dysplasia underlines the high-risk profile of this subgroup of patients with inflammatory bowel disease. The possible advantages of colon-sparing treatment should be balanced with the higher risk of metachronous CRC and the subsequent need for stringent endoscopic surveillance.
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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".