Long-term safety of rituximab in rheumatoid arthritis: 9.5-year follow-up of the global clinical trial programme with a focus on adverse events of interest in RA patients
Bibliographic record
Abstract
OBJECTIVES: Evaluation of long-term safety of rituximab in rheumatoid arthritis (RA). METHODS: Pooled observed case analysis of data from patients with moderate-to-severe, active RA treated with rituximab in a global clinical trial programme. RESULTS: As of September 2010, 3194 patients had received up to 17 rituximab courses over 9.5 years (11 962 patient-years). Of these, 627 had >5 years' follow-up (4418 patient-years). A pooled placebo population (n=818) (placebo+methotrexate (MTX)) was also analysed. Serious adverse event and infection rates generally remained stable over time and multiple courses. The overall serious infection event (SIE) rate was 3.94/100 patient-years (3.26/100 patient-years in patients observed for >5 years) and was comparable with placebo+MTX (3.79/100 patient-years). Serious opportunistic infections were rare. Overall, 22.4% (n=717) of rituximab-treated patients developed low immunoglobulin (Ig)M and 3.5% (n=112) low IgG levels for ≥4 months after ≥1 course. SIE rates were similar before and during/after development of low Ig levels; however, in patients with low IgG, rates were higher than in patients who never developed low IgG. Rates of myocardial infarction and stroke were consistent with rates in the general RA population. No increased risk of malignancy over time was observed. CONCLUSIONS: This analysis demonstrates that rituximab remains generally well tolerated over time and multiple courses, with a safety profile consistent with published data and clinical trial experience. Overall, the findings indicate that there was no evidence of an increased safety risk or increased reporting rates of any types of adverse events with prolonged exposure to rituximab during the 9.5 years of observation.
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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 | 0.026 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".