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Record W3000465228 · doi:10.1093/ecco-jcc/jjz203.641

P512 Efficacy of tofacitinib for the treatment of moderate-to-severe ulcerative colitis: real-world data

2020· article· en· W3000465228 on OpenAlexaffabout
Yasi Xiao, Péter L. Lakatos, Raymond Bourdages, Alain Bitton, Waqqas Afif, Rita Kohen, M Berberi, Talat Bessissow

Bibliographic record

VenueJournal of Crohn s and Colitis · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcGill University
Fundersnot available
KeywordsTofacitinibMedicineUlcerative colitisInternal medicineCalprotectinJanus kinase inhibitorGastroenterologyAdalimumabSurgeryInflammatory bowel diseaseTumor necrosis factor alphaRheumatoid arthritisDisease

Abstract

fetched live from OpenAlex

Abstract Background A significant proportion of patients do not respond to therapy for moderate to severe ulcerative colitis (UC), including thiopurines, glucocorticoids, and antagonists to tumour necrosis factor-a and integrin. Tofacitinib, a Janus Kinase inhibitor, has emerged as an efficacious and safe treatment for moderate to severe ulcerative colitis. However, data on its real-life efficacy remains sparse. Methods We aimed to assess the rate of clinical response and clinical remission at 3 and 6 months after tofacitinib initiation. Secondary endpoints included the rate of biomarker normalisation, corticosteroids-free clinical remission and severe infections. We conducted a multi-centre retrospective observational study of adult patients with active UC started on tofacitinib from January 1, 2015 to October 1, 2019 at the McGill University Health Center and Hotel-Dieu de Lévis. A positive clinical response was defined as a decrease of ≥3 in the partial Mayo score. Clinical remission was defined as partial Mayo score of ≤2. Biomarker normalisation was defined as faecal calprotectin ≤250 μg/g. Severe infection was defined as an infection requiring hospitalisation. Results During the study period, 40 patients with UC were started on tofacitinib at 10 mg/kg twice a day. Amongst the patients, 85% (n = 34) had failed ≥1 biologic and 50% (n = 20) had failed ≥3 biologics. At the time of this preliminary analysis, 38 patients had undergone 3 months of treatment; 30 patients had undergone 6 months of treatment. At 3 months, a clinical response was seen in 89.5% of patients (n = 34) and clinical remission occurred in 63.2%(n = 24). At 6 months, clinical response occurred in 73.3% of patients (n = 22) and clinical remission was sustained in 53.33% (n = 16). Biochemical normalisation occurred in 29.0% (n = 11) and 30.0% (n = 9) at 3 and 6 months respectively. Additionally, 63.2% (n = 24) of patients and 43.3% (n = 13) of patients achieved steroid-free clinical remission at 3 and 6 months respectively. In the interim, one patient developed a serious infection requiring discontinuation of the drug. Conclusion Our preliminary analysis demonstrates that in a real-life setting, tofacitinib is an effective treatment for inducing clinical remission in refractory UC patients. Further data will be complied to better assess the efficacy over a longer follow-up.

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)0.008
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 score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.034
GPT teacher head0.303
Teacher spread0.268 · 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".

Quick stats

Citations5
Published2020
Admission routes2
Has abstractyes

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