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Record W4206932095 · doi:10.1093/ecco-jcc/jjab232.114

DOP75 Effectiveness and Safety of tofacitinib versus vedolizumab in Patients with Ulcerative Colitis; A Nationwide, ICC Registry study

2022· article· en· W4206932095 on OpenAlexaff
Tessa Straatmijer, Marijn C. Visschedijk, Andrica de Vries, Frank Hoentjen, Ad A. van Bodegraven, Alexander Bodelier, Nanne K.H. de Boer, Gerard Dijkstra, Eleonora A. Festen, Carmen S. Horjus, Jeroen M. Jansen, Bindia Jharap, Wout Mares, Bas Oldenburg, Cyriel Y. Ponsioen, Tessa E H Römkens, Nidhi Srivastava, M M van der Voorn, Rachel West, C. Janneke van der Woude, M D J Wolvers, Marieke Pierik, Marjolijn Duijvestein

Bibliographic record

VenueJournal of Crohn s and Colitis · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVedolizumabTofacitinibMedicineUlcerative colitisInternal medicineFaecal calprotectinInflammatory bowel diseaseGastroenterologyPouchitisPropensity score matchingCalprotectinDiseaseRheumatoid arthritis

Abstract

fetched live from OpenAlex

Abstract Background Clinicians face difficulty in positioning biologics and JAK inhibitors in anti-TNF refractory ulcerative colitis (UC) patients. Head-to-head trials comparing the efficacy of vedolizumab and tofacitinib in UC patients are lacking. We aimed to compare the effectiveness and safety of vedolizumab and tofacitinib in anti-TNF experienced UC patients in our prospective, nationwide registry using a propensity score weighted cohort. Methods UC patients who failed anti-TNF treatment (with or without thiopurine) and initiated vedolizumab or tofacitinib treatment subsequently, were identified in the observational prospective Initiative on Crohn and Colitis (ICC) Registry. We selected patients with both clinical (Simple Clinical Colitis Activity Index (SCCAI) >2) and biochemical (C-reactive protein (CRP) >5mg/L or faecal calprotectin (FC) >250 µg/g) or endoscopic disease activity (endoscopic MAYO score ≥ 1) at initiation of therapy. Patients previously treated with vedolizumab or tofacitinib were excluded. Corticosteroid-free clinical remission (SCCAI<2), biochemical remission (CRP ≤5 mg/L and/or FC ≤250 µg/g) and safety outcomes were compared after 52 weeks of treatment. Inverse propensity scores weighted comparison was used to adjust for confounding and selection bias. Results Overall, 83 vedolizumab and 65 tofacitinib treated patients were included (table 1). Propensity score weighted analysis showed that tofacitinib treated patients were more likely to achieve corticosteroid-free clinical remission at week 12, 24 and 52 compared to vedolizumab treated patients (OR: 5.87, 95%CI:3.55–9.70, P<0.01, OR: 2.96, 95%CI: 1.85–4.73, P<0.01 and OR 2.96, 95%CI: 1.85–4.73, P<0.01, respectively) (table 2). In addition, tofacitinib treated patients were more likely to achieve biochemical remission at week 12 and week 24, remaining only statistically borderline at week 52 (OR: 2.96, 95%CI: 1.85–4.73, P<0.01, OR: 2.96, 95%CI: 1.85–4.73, P<0.01 and OR 1.68, 95%CI: 0.99–2.86, P=0.05, respectively) (table 2). There was no difference in infection rate (OR:1.057, 95%CI: 0.60–1.86, p=0.85) or severe adverse events (OR: 0.39, 95%CI: 0.03–4.33, P=0.44). No thromboembolic events were observed. Most common reason for treatment discontinuation was loss of response (table 3). Conclusion In tofacitinib treated, anti-TNF experienced, UC patients, we observed that a higher proportion of patients achieved corticosteroid-free remission after 12, 24 and 52 weeks compared to vedolizumab treated patients. In addition, more tofacitinib treated patients achieved biochemical remission at week 12 and 24. There was no statistically significant difference in severe adverse events.

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.237
Teacher spread0.231 · 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 designObservational
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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Citations0
Published2022
Admission routes1
Has abstractyes

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