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Record W4406698665 · doi:10.1093/ecco-jcc/jjae190.1235

P1061 A matching-adjusted indirect comparison (MAIC) of vedolizumab vs risankizumab in patients with moderately-to-severely active Crohn’s disease

2025· article· en· W4406698665 on OpenAlexaff
Vipul Jairath, Parambir S. Dulai, Paul Talsma, Jinhong Wu, S Adsul

Bibliographic record

VenueJournal of Crohn s and Colitis · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineVedolizumabCrohn's diseaseInternal medicineGastroenterologyDisease

Abstract

fetched live from OpenAlex

Abstract Background Crohn’s disease (CD), a chronic inflammatory bowel disease, requires effective therapies to manage symptoms and prevent complications. Vedolizumab (VDZ; a gut selective anti-α4β7-integrin) and risankizumab (RZB; anti-interleukin-23 p19) are approved for treatment of moderately-to-severely active CD. This matching-adjusted indirect comparison (MAIC) compared the efficacy of VDZ vs RZB using data from 5 phase 3 placebo (PBO)-controlled similarly designed clinical trials (GEMINI 2, VISIBLE 2, ADVANCE, MOTIVATE, FORTIFY).1-4 Methods Individual patient data from VDZ trials (GEMINI 2, VISIBLE 2)1,2 were adjusted for the observed cross-trial differences in patient baseline characteristics to match the aggregated data from RZB trials (ADVANCE, MOTIVATE, FORTIFY) following MAIC guidance from the National Institute for Health Care Excellence (NICE, 2016) using a method-of-moments-based matching approach.3,4 The baseline covariates used in the matching include potential effect modifiers and clinically relevant covariates that improved the balance across trials. Outcomes compared included Crohn’s Disease Activity Index (CDAI) response (decrease of CDAI of ≥ 100 points from baseline) or remission (CDAI ≤ 150). For induction, the CDAI outcomes were commonly available at Week 4, hence we compared between VDZ and the pooled RZB (ADVANCE + MOTIVATE) on the approved dosage anchoring on PBO as the common comparator. For maintenance, CDAI outcomes at Week 52 of VDZ (pooled GEMINI 2 + VISIBLE 2) were compared with each approved RZB maintenance dose (FORTIFY) anchoring PBO as the common comparator. Outcome differences were reported using the effect measure based on the risk differences in PBO-adjusted response rate. Results After matching, baseline characteristics in the induction and maintenance datasets were balanced between VDZ and RZB cohorts (Table). The relative treatment differences were numerically lower with VDZ vs RZB for CDAI response and remission early in induction phase at Week 4 (Figure). At Week 52, the relative treatment effect in CDAI response and remission for VDZ were similar to both RZB doses (Figure). The relative treatment difference in CDAI clinical remission were numerically higher for VDZ than RZB regardless of the dose (180 mg: 2.8% [95% CI -12.3%-18.0%]; 360 mg: 5.4% [-10.1%, 20.9%]). Conclusion Despite the numerically lower CDAI outcomes with VDZ early in induction at Week 4, the CDAI outcomes, especially the clinically more meaningful CDAI remission at Week 52 were comparable between VDZ and both RZB doses. Although direct comparisons are warranted to validate these results, this information may help clinicians make informed treatment decisions for patients with CD. References 1.D’Haens G, et al. Lancet. 2022;399(10340):2015-2030. 2. Ferrante M, et al. Lancet. 2022;399(10340):2031-2046. 3. Sandborn W.J, et al. N Engl J Med. 2013;369(8):711-721. 4. Vermeire S, et al. J Crohns Colitis. 2022;16(1):27-38.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.023
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0030.009
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.001

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.

Opus teacher head0.007
GPT teacher head0.239
Teacher spread0.232 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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