Patterns of tocilizumab use, effectiveness and safety in patients with rheumatoid arthritis: core data results from a set of multinational observational studies.
Bibliographic record
Abstract
OBJECTIVES: To observe patients with rheumatoid arthritis (RA) treated with the interleukin-6 receptor-alpha inhibitor tocilizumab (TCZ) in routine clinical practice. METHODS: Data on concomitant medications, effectiveness and safety were pooled from independent, multinational studies in patients with RA initiating intravenous TCZ according to local label recommendations observed in routine practice for 6 months. Patients were grouped by TCZ monotherapy or combination therapy with conventional synthetic disease-modifying anti-rheumatic drugs (csDMARDs). The primary endpoint was the proportion of patients receiving TCZ after 6 months. RESULTS: Of 1336 patients enrolled, 506 (37.9%) received TCZ monotherapy and 830 (62.1%) received combination therapy. Kaplan-Meier analysis estimated that 80% (95% CI, 76%-83%) of monotherapy and 87% (95% CI, 84%-89%) of combination therapy patients continued to receive TCZ at 6 months (log-rank p<0.001). During the observation period, TCZ was discontinued by 113 (22.3%) monotherapy patients and 116 (14.0%) patients on combination therapy. The mean prednisone-equivalent oral corticosteroid dose was 8.4 mg/day for monotherapy and combination therapy patients at baseline and 7.7 and 7.6 mg/day, respectively, at month 6. Adverse events or laboratory abnormalities requiring TCZ dose modification were reported for 66 (13.0%) monotherapy and 130 (15.7%) combination therapy patients. Effectiveness at 6 months was similar between groups; mean (SD) change from baseline in Clinical Disease Activity Index (CDAI) was -20.3 (14.18) for monotherapy and -22.3 (16.09) for combination therapy (p=0.7347). CONCLUSIONS: In routine clinical practice, 38% of patients received TCZ as monotherapy. Persistence on monotherapy or in combination therapy with csDMARDs was high, with a slight trend towards a higher rate with combination therapy, and effectiveness was similar between groups.
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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 | 0.015 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| 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".