Combination leflunomide and methotrexate (MTX) therapy for patients with active rheumatoid arthritis failing MTX monotherapy: open-label extension of a randomized, double-blind, placebo controlled trial.
Bibliographic record
Abstract
OBJECTIVE: To obtain additional safety and efficacy data on leflunomide (LEF) treatment in combination with methotrexate (MTX) therapy in an open-label extension study in patients with rheumatoid arthritis (RA). METHODS: Following a 24 week, randomized, double-blind trial of adding placebo (PLA) or LEF to stable MTX therapy, patients could enter a 24 week extension. Subjects randomized to LEF and MTX continued treatment [(LEF/LEF) + MTX]. Subjects randomized to PLA and MTX switched to LEF (10 mg/day, no loading dose) and MTX [(PLA/LEF) + MTX]. The double-blind regarding initial randomization was maintained. RESULTS: For subjects in the extension phase, American College of Rheumatology 20% (ACR20) responder rates for the (LEF/LEF) + MTX group were maintained from Week 24 (57/96, 59.4%) to Week 48 (53/96, 55.2%). ACR20 responder rates improved in patients switched to LEF from PLA at Week 24 [(PLA/LEF) + MTX] from 25.0% (24/96) at Week 24 to 57.3% (55/96) at Week 48. Patients in the extension who switched from PLA to LEF without a loading dose exhibited a lower incidence of elevated transaminases compared to patients initially randomized to LEF. Diarrhea and nausea were less frequent during the open-label extension in patients who did not receive a LEF loading dose. CONCLUSION: Response to therapy was maintained to 48 weeks of treatment in patients who continued to receive LEF and MTX during the extension. Importantly, ACR20 response rates after 24 weeks of LEF therapy were similar between patients switched from PLA to LEF without loading dose, and those who received a loading does of LEF (100 mg/day x 2 days) at randomization. Fewer adverse events were reported in patients switched to LEF without a loading dose.
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".