Tocilizumab Patterns of Use, Effectiveness, and Safety in Patients with Rheumatoid Arthritis: Final Results from a Set of Multi-National Non-Interventional Studies
Bibliographic record
Abstract
INTRODUCTION: The objective of this study was to observe the patterns of usage, efficacy, and safety of tocilizumab (TCZ) in clinical practice in patients with rheumatoid arthritis. METHODS: Data on the real-world usage, efficacy, and safety of TCZ were collected from patients during routine follow-up visits conducted over a 6-month period. Patients were grouped by previous exposure to biologic therapies (biologic exposed vs. biologic naive). RESULTS: Of 1912 patients enrolled from 16 countries, 639 (33.4%) received TCZ monotherapy and 1273 (66.6%) received TCZ combination therapy. At baseline, 1073 patients (56.1%) were biologic naive and 839 (43.9%) were biologic exposed. At 6 months, 1504 patients (78.7%) continued to receive TCZ treatment, with no descriptive differences in retention rates between biologic-exposed and biologic-naive patients and between patients receiving TCZ monotherapy or combination therapy. Dose and use of methotrexate and prednisone were reduced at 6 months. Efficacy at 6 months, including patient-reported outcomes, was demonstrated in both biologic-naive and biologic-exposed groups. Adverse events (AEs) occurred in 817 patients [42.7%; incidence rate: 179 events per 100 patient-years (PY)], and serious AEs (SAEs) occurred in 118 patients (6.2%; 17 events per 100 PY), with comparable rates of AEs and SAEs between subgroups. CONCLUSION: In routine clinical practice, TCZ discontinuation rates were low and unaffected by prior use of biologics. Effectiveness was similar between groups, and no new safety signals were identified. FUNDING: F. Hoffmann-La Roche.
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 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".