The SMILE Study — Safety of Methotrexate in Combination with Leflunomide in Rheumatoid Arthritis
Bibliographic record
Abstract
OBJECTIVE: To assess the safety of treating patients with rheumatoid arthritis with a combination of methotrexate (MTX) and leflunomide (LEF) in comparison to MTX monotherapy, in clinical practice. METHODS: The Safety of Methotrexate in Combination with Leflunomide in Rheumatoid Arthritis (SMILE) study was a multicenter, observational, cross-sectional, retrospective safety study. The study was conducted by the Optimising Patient Outcomes in Australian Rheumatology-Quality Use of Medicines Initiative (OPAL QUMI). Data were deidentified for patient, clinic, and clinician prior to collection from 13 participating rheumatology practices (25 rheumatologists). Comparative analysis of safety for the different treatments, primarily with regard to neutropenia and liver abnormalities, was performed. RESULTS: In total, 2975 patients were included in the study: 74% female, 26% male, mean age 62 years (SD 13.6). Distribution of therapy: MTX monotherapy 52.2%, LEF monotherapy 7.3%, MTX plus LEF 13.9%, and neither MTX nor LEF 26.6%. Comorbid liver disease was reported in 8.1% of patients. Liver function abnormalities were reported in 12% of the MTX monotherapy group, 16% of the LEF monotherapy group, 19% of the MTX-LEF combination group, and 14% of the group not taking either drug. Neutropenia was reported in 2.3% of the MTX monotherapy group, 5.5% of the LEF monotherapy group, 3.9% of the MTX-LEF combination group, and 4.2% of the group not taking either drug. CONCLUSION: The combination of MTX and LEF was well tolerated, with adverse events comparable to those of monotherapy and the other nonbiologic disease-modifying antirheumatic drug treatment group.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".