Long-Term Effectiveness and Safety of Infliximab, Golimumab and Golimumab-IV in Rheumatoid Arthritis Patients from a Canadian Prospective Observational Registry
Bibliographic record
Abstract
Abstract Background: Long-term clinical registries are essential tools to evaluate new therapies in a patient population that differs from those in randomized clinical trials. The objectives are to describe the profile of rheumatoid arthritis (RA) patients treated with anti-TNF agents in Canadian routine care.Methods: RA patients eligible for treatment with Infliximab (IFX), golimumab (GLM) or intravenous golimumab (GLM-IV) as per their respective Canadian product monographs were enrolled into the BioTRAC registry between 2002 and 2017. Study visits occurred at baseline and every 6 months thereafter. Effectiveness was assessed by changes in disease activity. Safety was evaluated by the incidence of adverse events (AEs) and drug survival.Results: Of the 890 IFX-, 530 GLM-SC- and 157 GLM-IV-treated patients, the proportion of females ranged from 77.0-86.6%, the mean ages from 55.8-57.7 and the mean disease duration from 6.5-8.6 years. A significant decrease in baseline disease duration and disease activity parameters (DAS, TJC, SJC, HAQ, AM stiffness, MDGA, PtGA, CRP, ESR) was observed over time. Treatment with IFX, GLM-SC and GLM-IV significantly improved all disease parameters over time. The incidence of AEs was 105, 113 and 82.6 /100 PYs and the incidence of SAEs was 11.7, 11.2 and 4.68 /100 PYs for IFX, GLM-SC and GLM-IV-treated patients, respectively. Conclusion: Differences in baseline characteristics between patients treated with an anti-TNFs over time shows the evolution of treatment modalities over time. All treatments significantly reduced disease activity and improved functionality in a similar fashion. The incidence of adverse events was consistent with the safety profiles of IFX and GLM.Trial Registration: 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 | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".