Efalizumab for the Treatment of Psoriatic Arthritis
Bibliographic record
Abstract
BACKGROUND: Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. Efalizumab, a T cell-targeted, recombinant human monoclonal antibody, is approved for the treatment of adult patients with chronic moderate to severe plaque psoriasis. The effect of efalizumab therapy on PsA has not previously been investigated. OBJECTIVE: This phase II randomized, double-blind, placebo-controlled multicenter study evaluated the efficacy and safety of efalizumab for the treatment of PsA. METHODS: Patients were required to be on at least one of the following concomitant systemic therapies for PsA: nonsteroidal anti-inflammatory drugs, corticosteroids, and/or sulfasalazine or methotrexate. One hundred fifteen patients with active PsA were enrolled and randomized in the study. Of these, 107 were treated weekly with efalizumab 1 mg/kg or placebo for 12 weeks, followed by 12 additional weeks of open-label efalizumab. RESULTS: At week 12, 28% of efalizumab-treated patients achieved ACR-20 response (a 20% reduction from the baseline in the American College of Rheumatology response criteria), the primary end point, compared with 19% of placebo patients (p = .27). The safety profile was comparable between efalizumab- and placebo-treated patient groups, regardless of methotrexate background therapy, and no worsening of joint disease occurred with efalizumab therapy. CONCLUSIONS: Efalizumab was not effective in treating PsA; efalizumab therapy did not worsen PsA. The efalizumab safety profile does not appear to be altered with the concomitant use of methotrexate therapy.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".