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Record W4281857406 · doi:10.1002/acr.24966

Effectiveness and Safety of Tofacitinib in Canadian Patients With Rheumatoid Arthritis: Primary Results From a Prospective Observational Study

2022· article· en· W4281857406 on OpenAlexafffundabout
Boulos Haraoui, Majed Khraishi, D. Choquette, Larissa Lisnevskaia, Michelle Teo, C. Kinch, Corina Galos, Patrice Roy, David Gruben, John Woolcott, Julie Vaillancourt, John S. Sampalis, Edward Keystone

Bibliographic record

VenueArthritis Care & Research · 2022
Typearticle
Languageen
FieldMedicine
TopicRheumatoid Arthritis Research and Therapies
Canadian institutionsUniversity of TorontoPfizer (Canada)GDI Integrated Facility Services (Canada)Penticton Regional HospitalMcGill UniversityLakeridge HealthUniversity of British ColumbiaMemorial University of Newfoundland
FundersPfizer CanadaPfizer
KeywordsMedicineTofacitinibRheumatoid arthritisInternal medicineObservational studyErythrocyte sedimentation ratePhysical therapyMinimal clinically important differenceVisual analogue scaleInterim analysisConcomitantProspective cohort studyClinical trialRandomized controlled trial

Abstract

fetched live from OpenAlex

OBJECTIVE: The Canadian Tofacitinib for Rheumatoid Arthritis Observational (CANTORAL) is the first Canadian prospective, observational study assessing tofacitinib. The objective was to assess effectiveness and safety for moderate to severe rheumatoid arthritis (RA). Coprimary and secondary outcomes are reported from an interim analysis. METHODS: Patients initiating tofacitinib from October 2017 to July 2020 were enrolled from 45 Canadian sites. Coprimary outcomes (month 6) included the Clinical Disease Activity Index (CDAI)-defined low disease activity (LDA) and remission. Secondary outcomes (to month 18) included the CDAI and the 4-variable Disease Activity Score in 28 joints (DAS28) using the erythrocyte sedimentation rate (ESR)/C-reactive protein (CRP) level to define LDA and remission; the proportions of patients achieving mild pain (visual analog scale <20 mm), and moderate (≥30%) and substantial (≥50%) pain improvements; and the proportions of patients achieving a Health Assessment Questionnaire disability index (HAQ DI) score greater or equal to normative values (≤0.25) and a HAQ DI score greater or equal to minimum clinically important difference (MCID) (≥0.22). Safety was assessed to month 36. RESULTS: Of 504 patients initiating tofacitinib, 44.4% received concomitant methotrexate. At month 6, 52.9% and 15.4% of patients were in CDAI-defined LDA and remission, respectively; a similar proportion of patients achieved outcomes by month 3 (first post-baseline assessment). By month 3, 27.2% and 41.7% of patients, respectively, were in DAS28-ESR-defined LDA and DAS28-CRP <3.2; 14.7% and 25.8% achieved DAS28-ESR remission and DAS28-CRP <2.6. By month 3, mild pain and moderate and substantial pain improvements occurred in 29.6%, 55.6%, and 42.9% of patients, respectively; 19.9% and 53.7% of patients achieved a HAQ DI score greater than or equal to normative values and a HAQ DI score greater than or equal to MCID, respectively. Outcomes were generally maintained to month 18. Incidence rates (events per 100 patient-years) for treatment-emergent adverse events (AEs), serious AEs, and discontinuations due to AEs were 126.8, 11.9, and 14.5, respectively, and AEs of special interest were infrequent. CONCLUSION: Tofacitinib was associated with early and sustained improvement in RA signs and symptoms in real-world patients. Effectiveness and safety were consistent with the established tofacitinib clinical profile.

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 score0.138
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.004
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.299
Teacher spread0.274 · 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

Citations9
Published2022
Admission routes3
Has abstractyes

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