DECIDE: Delphi Expert Consensus Statement on Inflammatory Bowel Disease Dysplasia Shared Management Decision-Making
Bibliographic record
Abstract
BACKGROUND AND AIMS: Inflammatory bowel disease colitis-associated dysplasia is managed with either enhanced surveillance and endoscopic resection or prophylactic surgery. The rate of progression to cancer after a dysplasia diagnosis remains uncertain in many cases and patients have high thresholds for accepting proctocolectomy. Individualised discussion of management options is encouraged to take place between patients and their multidisciplinary teams for best outcomes. We aimed to develop a toolkit to support a structured, multidisciplinary and shared decision-making approach to discussions about dysplasia management options between clinicians and their patients. METHODS: Evidence from systematic literature reviews, mixed-methods studies conducted with key stakeholders, and decision-making expert recommendations were consolidated to draft consensus statements by the DECIDE steering group. These were then subjected to an international, multidisciplinary modified electronic Delphi process until an a priori threshold of 80% agreement was achieved to establish consensus for each statement. RESULTS: In all, 31 members [15 gastroenterologists, 14 colorectal surgeons and two nurse specialists] from nine countries formed the Delphi panel. We present the 18 consensus statements generated after two iterative rounds of anonymous voting. CONCLUSIONS: By consolidating evidence for best practice using literature review and key stakeholder and decision-making expert consultation, we have developed international consensus recommendations to support health care professionals counselling patients on the management of high cancer risk colitis-associated dysplasia. The final toolkit includes clinician and patient decision aids to facilitate shared decision-making.
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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 | 0.359 | 0.344 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.006 | 0.021 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".