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Record W4406705244 · doi:10.1093/ecco-jcc/jjae190.0041

DOP002 Efficacy and safety of upadacitinib after 4 years of treatment in patients with moderately to severely active ulcerative colitis: interim long-term data from the phase 3 open-label extension study (U-ACTIVATE)

2025· article· en· W4406705244 on OpenAlexaff
Remo Panaccione, Gary Lichtenstein, Jean‐Frédéric Colombel, Hiroshi Nakase, Xuan Yao, Justin Klaff, Michelle Kujawski, Lorenzo Rizzo, Smitha Suravaram, Séverine Vermeire

Bibliographic record

VenueJournal of Crohn s and Colitis · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineUlcerative colitisOpen labelInterimInterim analysisInternal medicineClinical trialGastroenterologySurgery

Abstract

fetched live from OpenAlex

Abstract Background Upadacitinib (UPA), an oral, reversible Janus kinase inhibitor approved for the treatment of ulcerative colitis (UC),1,2 has shown sustained efficacy and an acceptable safety profile in long-term studies of immune-mediated diseases.3,4 Methods We report efficacy and safety of UPA from the U-ACTIVATE (NCT03006068) long-term extension (LTE). Patients (pts) had approximately 4 years (yrs) of maintenance therapy, consisting of 1-yr U-ACHIEVE maintenance and 3 yrs LTE. Pts were randomised to placebo (PBO) or UPA 45 mg once daily (QD) for the 8-week (wk) induction. Clinical responders were re-randomised to PBO, UPA 15 mg QD (UPA15), or UPA 30 mg QD (UPA30) for the 52-wk maintenance. Pts in clinical remission (CR) per Adapted Mayo score (AMS) at wk 52 of the maintenance study continued their double-blind treatment upon entering the LTE. Non-remitters originally randomised to UPA15 were eligible to escalate to UPA30, those randomised to blinded UPA30 continued on blinded UPA30, and those assigned to PBO were eligible to escalate to UPA15 in a blinded manner; see footnote for additional information (Table 1). The study was not designed to compare UPA15 and UPA30 doses. Efficacy was evaluated by CR (per AMS and Partial Mayo score), maintenance of CR per AMS, endoscopic improvement (EI), maintenance of EI, endoscopic remission (ER), and maintenance of ER during the LTE at wk 144. Efficacy data are presented as observed (AO), as well as modified non-responder imputation (mNRI). Treatment-emergent adverse events (TEAEs) were presented as exposure-adjusted event rates (EAERs; events per 100 pt yrs [E/100 PY]); cut-off date: June 30, 2024. Results At LTE wk 144, improvements in CR per AMS and maintenance of CR per AMS were observed in more than half of pts treated with UPA15 or UPA30 (Table 1). ER was achieved by nearly half of pts and more than half of pts maintained ER at LTE wk 144 with UPA15 and UPA30. For safety, 369 pts (UPA15, N=142; UPA30, N=227) with 1043.5 PY (UPA15, 397.4 PY; UPA30, 646.1 PY) of exposure to UPA were analysed (Table 2). Rates of serious TEAEs and TEAEs leading to treatment discontinuation were similar across treatment groups. There was 1 TEAE leading to death (EAER: 0.2 E/100 PY) in a pt requiring prolonged hospitalisation for worsening COVID-19 infection in the UPA30 group. Conclusion Pts achieved and maintained key clinical and endoscopic outcomes through 4 yrs of UPA treatment. Response rates based on mNRI were consistent with the AO approach, supporting the long-term efficacy of UPA. The long-term safety profile for UPA in pts with UC was consistent with previous analyses,1,2 with no new safety risks identified in the ongoing LTE study. These analyses continue to support the favourable benefit–risk in pts with UC. References 1. Danese S, et al. Lancet 2022;399:2113–28 2. Vermeire S, et al. Lancet Gastroenterol Hepatol 2023;8:976–89 3. Fleischmann R, et al. RMD Open 2022;8:e002012 4. Simpson EL, et al. JAMA Dermatol 2022;158:404–13

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)0.003
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.026
GPT teacher head0.322
Teacher spread0.296 · 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 designNon-randomized trial
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".

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Citations3
Published2025
Admission routes1
Has abstractyes

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