Long-term effectiveness and safety of infliximab, golimumab and ustekinumab in patients with psoriatic arthritis from a Canadian prospective observational registry
Bibliographic record
Abstract
OBJECTIVES: The objectives of this study were to describe the demographic profile and baseline disease characteristics of patients with psoriatic arthritis (PsA) treated with either infliximab (IFX), subcutaneous golimumab (GLM) or ustekinumab (UST) treatment in Canadian routine care setting along with assessing long-term effectiveness and safety. METHODS: Patients with PsA were enrolled into the Biologic Treatment Registry Across Canada registry (ClinicalTrials.gov Identifier: NCT00741793) from 2005 to 2017. The study visits occurred at study enrolment (baseline) and every 6 months thereafter. Effectiveness was assessed by changes in disease parameters (joint counts, Psoriasis Area Severity Index (PASI), Health Assessment Questionnaire, patient/physician global, minimal disease activity, enthesitis, dactylitis, erythrocyte sedimentation rate, C reactive protein). Improvements from baseline were explored with the paired t-test and the McNemar's test. Safety was evaluated by assessing the incidence of adverse events (AEs) and drug survival rates. RESULTS: A total of 111 IFX-treated, 281 GLM-treated and 70 UST-treated patients were enrolled. Most baseline disease parameters remained similar over time in all three cohorts. UST-treated patients had lower mean baseline Disease Activity Score in 28 joints CRP, swollen joint based on 28 joints and higher PASI compared with patients treated with GLM. Treatment with IFX, GLM and UST was associated with significant improvements in all disease parameters over time (p<0.001) from baseline up to 84, 84 and 40 months, respectively.AEs were reported for 74.8%, 69.8% and 52.9% (138, 114 and 115 events/100 patient-years (PYs)) covering 325, 567 and 87 years of exposure for IFX-treated, GLM-treated and UST-treated patients, respectively. Severe AEs were reported in 19.8%, 8.5% and 5.7% (8.8, 7.2 and 8.0 events/100 PYs) in IFX-treated, GLM-treated and UST-treated patients, respectively. The proportion of patients who discontinued treatment were 63.1%, 50.9% and 50.0%, respectively. CONCLUSIONS: IFX, GLM and UST treatment significantly reduced disease activity and improved functionality in patients with PsA followed by routine clinical practice and had a safety profile similar to that previously reported in the literature. TRIAL REGISTRATION NUMBER: NCT00741793.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".