P115 Efficacy of mirikizumab in comparison to ustekinumab in patients with moderate-to-severe Crohn’s disease: results from phase 3 VIVID 1 study
Bibliographic record
Abstract
Objective Here we compared mirikizumab (miri), a p19-directed anti-IL-23 antibody, to ustekinumab (uste), a p40 directed anti-IL-12/IL-23 inhibitor, from the Phase 3, randomised, double-blind, double-dummy, active- and PBO-controlled, treat-through (TT) study, VIVID-1 (NCT03926130). Methods Adult pts (N=1065) were randomised 6:3:2 to miri (N=579) 900mg intravenously (IV) every 4 weeks (Q4W) to W12, then 300mg subcutaneously (SC) Q4W to W52, uste (N=287) one ~6 mg/kg IV dose, then 90mg SC Q8W to W52 or PBO (N=199). Results Pts treated with miri achieved all key major secondary endpoints (p<.000001) compared to PBO. Miri achieved non-inferiority to uste for clinical remission by Crohn’s Disease Activity Index (CDAI) (p=0.113117). Although superiority to uste in endoscopic response was not achieved (p=0.51), in biologic failed pts miri demonstrated a numerical trend towards greater response rates compared to uste for endoscopic response and clinical remission by CDAI. The overall safety profile was consistent with the known safety profile of miri. The proportion of treatment-emergent adverse events (TEAE) were similar for miri (78.6%) and uste (77.3%); most common TEAEs were COVID-19, anaemia, arthralgia, headache, upper respiratory tract infection, nasopharyngitis and injection-site reaction. Instances of serious adverse events were comparable for miri (10.3%) and uste (10.7%). Conclusion Miri achieved non-inferiority to uste for clinical remission by CDAI. In biologic-failed pts, miri had a numerical trend towards greater response compared to uste in clinical and endoscopic endpoints, with an acceptable safety profile.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".