Combination of Methotrexate and Leflunomide Is Safe and Has Good Drug Retention Among Patients With Psoriatic Arthritis
Bibliographic record
Abstract
To the Editor: Psoriatic arthritis (PsA) is a potentially progressive immune-mediated musculoskeletal disease with the involvement of synovium, enthesis, and axial structures (especially the cervical spine and sacroiliac joints), along with the involvement of skin and nails. Even a short delay in the diagnosis and commencement of antirheumatic therapy can cause long-term damage and disabilities.1 However, there remains considerable confusion regarding the effectiveness of conventional synthetic (cs-) disease-modifying antirheumatic drugs (DMARDs), especially methotrexate (MTX), given the lack of high-level evidence to support its use in PsA.2 The availability of biologic DMARDs (bDMARDs) and targeted synthetic DMARDs have revolutionized the management of psoriatic disease3; however, for Pakistani patients, it comes with a significant cost burden. Unfortunately, being in a resource-poor country, access to biologic therapies is extremely limited. Hence, in our practice, we are inclined to use a combination of potent DMARDs after MTX failure, prior to considering biologic therapies (except in the scenario of very active axial disease or skin disease). We believe that a combination of DMARDs, especially that of MTX and leflunomide (LEF), provides a valuable low-cost treatment option for patients with PsA after failure of MTX monotherapy. Little is known about the combined use of LEF and MTX in PsA, especially in the context of drug retention time and tolerability.4 We aimed to review our PsA cohort data especially examining the drug retention of …
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".