Leflunomide in rheumatoid arthritis: recommendations through a process of consensus
Bibliographic record
Abstract
OBJECTIVES: To determine, by consensus, the optimal use of leflunomide in rheumatoid arthritis (RA), using a multidisciplinary panel of experts and performing meta-analyses of available data. METHODS: A multidisciplinary panel of experts in RA was convened. Important questions, pertinent to the use of leflunomide in the treatment of RA, were defined by consensus at an initial meeting. Each question was allocated to subgroups of two or three members, who worked separately to prepare a balanced opinion, based on published literature, data from individual patients taking part in phase II and phase III clinical trials provided by Aventis, and data from a USA-based medical claims database (AETNA). The full group then reconvened to agree on an overall consensus statement. Recommendations concerning efficacy and tolerability versus comparator drugs and placebo were derived from two new meta-analyses. RESULTS: Leflunomide was at least as effective as sulphasalazine and methotrexate, and equally well tolerated on meta-analysis of trial data. Overall withdrawal rates for all adverse events were similar for all three drugs. Avoidance of the loading dose reduces 'nuisance' side-effects (e.g. nausea), but probably delays the onset of action. Adverse events could usually be managed by dose reduction and/or symptomatic therapy. CONCLUSIONS: On the basis of efficacy, safety and cost, leflunomide should be considered in patients with RA who have failed first-line DMARD drug therapy. In refractory cases, leflunomide may be used in combination with, for example, methotrexate before biological agents. Therapy should be initiated by a specialist, but repeat prescribing in general practice on a shared care basis is acceptable using agreed protocols. Clear mechanisms are required to monitor toxicity, with good communication between the patient and rheumatologist to manage nuisance side-effects and avoid unnecessary discontinuation of leflunomide.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".