Endoscopic, Histologic, and Composite Endpoints in Patients With Ulcerative Colitis Treated With Etrasimod
Bibliographic record
Abstract
BACKGROUND & AIMS: receptor modulator for the treatment of moderately to severely active UC. This post-hoc analysis of the ELEVATE UC program evaluated the efficacy of etrasimod according to histologic and composite (histologic/endoscopic/symptomatic) endpoints and examined their prognostic value. METHODS: Patients with moderately to severely active UC were randomized 2:1 to once-daily oral etrasimod 2 mg or placebo. Histologic and composite endpoints, including disease clearance (endoscopic/histologic/symptomatic remission), were assessed at Weeks 12 (ELEVATE UC 52; ELEVATE UC 12) and 52 (ELEVATE UC 52). Logistic regressions examined associations between baseline and Week 12 histologic/composite endpoints and Week 52 outcomes. RESULTS: At Weeks 12 and 52, significant improvements with etrasimod vs placebo were observed in histologic/composite outcomes, including endoscopic improvement-histologic remission and disease clearance. The proportion of patients treated with etrasimod achieving clinical remission at Week 52 was higher among those with disease clearance at Week 12 vs those without disease clearance (73.9% [17/23] vs 28.3% [71/251]). Histologic improvement and endoscopic improvement at Week 12 were moderately and strongly associated with clinical remission at Week 52 (odds ratio [OR], 2.37; 95% confidence interval [CI], 1.27-4.41; and OR, 6.36; 95% CI, 3.47-11.64, respectively). Histologic remission and endoscopic improvement at Week 12 were strongly associated with endoscopic improvement-histologic remission at Week 52 (OR, 3.21; 95% CI, 1.70-6.06 and OR, 5.47; 95% CI, 2.89-10.36, respectively). CONCLUSIONS: Etrasimod was superior to placebo for achievement of stringent histologic and composite endpoints. CLINICALTRIALS: gov, Number: NCT03945188; ClinicalTrials.gov, Number: NCT03996369.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".