Disease-modifying Antirheumatic Drugs (DMARD) and Combination Therapy of Conventional DMARD in Patients with Spondyloarthritis and Psoriatic Arthritis with Axial Involvement
Bibliographic record
Abstract
Treatment with nonsteroidal antiinflammatory drugs (NSAID) is the recommended first-line therapy in patients with axial spondyloarthritis (axSpA); and for those patients who have persistently active disease, the introduction of tumor necrosis factor-α (TNF-α) inhibitors is indicated. Conventional nonbiological disease-modifying antirheumatic drugs (DMARD), although effective and used in clinical practice for peripheral arthritis, are not recommended. Few studies have been conducted with the aim of evaluating the effect of conventional DMARD, either alone or in combination, in axSpA. As for psoriatic arthritis (PsA), DMARD are widely used, but few trials are available about their effects on axial involvement, which is not often assessed as a primary outcome in clinical trials. In rheumatoid arthritis, combination therapy of 2 or more conventional DMARD appears to confer better response than methotrexate monotherapy, and may even be a viable alternative to TNF-α inhibitors. In peripheral PsA, combination therapy can be used after treatment failure with 1 DMARD, but few studies have been conducted. However, available evidence for the combination of conventional DMARD indicates a lack of any significant benefit on axial symptoms; thus this treatment approach does not represent an effective alternative to anti-TNF-α therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".