Etanercept in Psoriatic Arthritis
Bibliographic record
Abstract
In this update on etanercept (ETN) in psoriatic arthritis (PsA) we analyze this drug's mechanism of action, clinical efficacy/effectiveness, optimal dosage, disease-modifying antirheumatic drugs (DMARD) association, radiological progression, safety, switching aspects, and pharmacoeconomy. The efficacy/effectiveness of ETN in PsA has been demonstrated in randomized placebo-controlled trials as well as in observational studies representing routine clinical practice. At 1 and 2 years, ETN inhibited radiographic disease progression, assessed by the modified total Sharp score. ETN (generally at a dosage of 50 mg/weekly) can be used either in monotherapy or in combination with DMARD such as methotrexate. A systematic search of randomized, placebo-controlled trials of ETN to treat adults with plaque psoriasis or PsA suggests that the short-term risk/benefit ratio is favorable. Longterm studies, such as observational studies, confirmed this safety profile of ETN. A variable percentage of patients withdrew anti-tumor necrosis factor-α (TNF-α) inhibitor treatment owing to inefficacy or poor tolerability. Observational studies showed that in the case of treatment failure with 1 agent, switching to the other agent may also be useful in patients with PsA because of the different molecular structures and targets of available TNF-α blockers. The clinical effect of ETN is associated with favorable pharmacoeconomic considerations.
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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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".