Comparison of tocilizumab as monotherapy or with add-on disease-modifying antirheumatic drugs in patients with rheumatoid arthritis and inadequate responses to previous treatments: an open-label study close to clinical practice
Bibliographic record
Abstract
This was an exploratory analysis comparing the safety and efficacy of tocilizumab monotherapy with those of tocilizumab in combination with disease-modifying anti-rheumatic drugs (DMARDs). Data were from a single-arm, nonrandomized, open-label, 24-week study in patients with rheumatoid arthritis in which patients with inadequate responses to DMARDs or tumor necrosis factor-α inhibitors received tocilizumab 8 mg/kg intravenously every 4 weeks plus methotrexate/other DMARD(s) combination therapy. If they were intolerant of methotrexate/other DMARD, patients received tocilizumab monotherapy. Effectiveness endpoints included American College of Rheumatology (ACR) responses (ACR20/50/70/90) and disease activity score using 28 joints (DAS28). Of 1,681 patients, 239 received tocilizumab monotherapy, and 1,442 received combination therapy. Methotrexate was the most common DMARD (79%) used in combination therapy. The frequency of adverse events (AEs), serious AEs, and AEs leading to withdrawal were similar between tocilizumab monotherapy (82.4, 7.9, and 5.4%, respectively) and combination therapy (76.6, 7.8, and 5.1%, respectively). No differences in ACR20/50/70/90 responses were observed between treatment groups (66.9%/43.5%/23.8%/10.0% vs 66.9%/47.2%/26.8%/8.5%, respectively; p > 0.12 for all individual comparisons, including ACR50 propensity score analyses). The decrease in DAS28 was also similar between treatment groups (mean ± standard deviation: -3.41 ± 1.49 for tocilizumab monotherapy vs -3.43 ± 1.43 for combination therapy; p > 0.33 all analyses, including propensity score analyses). Tocilizumab had a comparable safety profile, and was similarly effective, when used as monotherapy or in combination with DMARDs in a broad population of patients with rheumatoid arthritis.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".