Outcomes of endoscopic submucosal dissection for high-risk colorectal colitis-associated neoplasia in inflammatory bowel disease
Bibliographic record
Abstract
BACKGROUND: Patients with inflammatory bowel disease (IBD) have an increased risk of colorectal cancer. High-risk colorectal colitis-associated neoplasia (HR-CAN) can be difficult to treat using traditional endoscopic resection methods. This study evaluated the outcomes of endoscopic submucosal dissection (ESD) in patients with IBD and HR-CANs. METHODS: This retrospective multicenter study consecutively included patients with IBD who were referred to expert Italian endoscopy centers for ESD or hybrid ESD (hESD) of HR-CANs. The main outcomes were rates of en bloc, R0, and curative resections, adverse events, local recurrence, metachronous lesions, and post-resection surgery. Kaplan-Meier method was used to analyze survival rates. Risk factors associated with the main outcomes were investigated by univariable analysis. RESULTS: 91 patients with colonic IBD (disease duration 15.3 [SD 8.7] years, 82.4 % with ulcerative colitis) with 96 HR-CANs (mean size 34.8 [SD 16.2] mm, 53.1 % high grade dysplasia/adenocarcinoma) were included. ESD and hESD were performed in 82.3 % and 17.7 %, respectively. En bloc, R0, and curative resections were achieved in 95.8 % (95 %CI 89.6-98.8), 85.4 % (95 %CI 76.7-91.7), and 83.3 % (95 %CI 74.3-90.1). Adverse events occurred in 12.5 % (95 %CI 6.6-20.8), which were all conservatively managed. After a mean follow-up of 23.4 (SD 16.1) months, local recurrence and metachronous lesions each occurred in 3.1 %. Post-resection surgery was required in 11.5 %. CONCLUSIONS: ESD of HR-CANs showed favorable outcomes on the medium- and long-term course in patients with IBD.
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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 | 0.002 |
| 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) | 0.001 | 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".