Effectiveness of etrasimod on disease activity and patient-reported outcomes in ulcerative colitis—EFFECT-UC: a non-interventional, multinational, prospective cohort study protocol
Bibliographic record
Abstract
INTRODUCTION: receptor modulator for the treatment of moderately to severely active ulcerative colitis (UC). While etrasimod demonstrated efficacy in randomised controlled trials, understanding its effectiveness in an observational setting is crucial. METHODS AND ANALYSIS: EFFECT-UC is a prospective, multinational, non-interventional study to evaluate the real-world effectiveness of etrasimod in adults with moderately to severely active UC. The study consists of a 52-week treatment period and a 28-day safety follow-up period and aims to enrol ~300 patients per cohort. Eligible patients (18-64 years) are advanced therapy naïve or experienced and are initiating etrasimod in a real-world clinical setting. Treatment will be guided independently by the clinician's judgement. Patient-reported outcomes will be collected electronically throughout the study and daily for the first 2 weeks. Exploratory data, including faecal calprotectin, endoscopy and intestinal ultrasound, will be collected at predefined visits or during standard care. Primary endpoints are symptomatic remission at week 12 and week 52. Secondary endpoints include patient-reported outcome 2 (combined rectal bleeding and stool frequency subscores) response at week 12 and week 52 and corticosteroid-free symptomatic remission at week 52. ETHICS AND DISSEMINATION: Ethics approval was obtained for all sites. Recruitment is underway for cohort 1, comprising patients from the UK, Germany and Canada. Interim results for this cohort are expected in 2026 and final results in 2028; these will be submitted for publication in peer-reviewed journals and presented at appropriate congresses. TRIAL REGISTRATION NUMBER: NCT06294925.
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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 | 0.022 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.007 |
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".