Novel approaches to biological therapy for psoriatic arthritis
Bibliographic record
Abstract
INTRODUCTION: Improved understanding of the immunopathogenic mechanisms in psoriatic arthritis (PsA) has led to the development of targeted biological therapies, which demonstrate superior clinical efficacy to traditional disease-modifying antirheumatic drugs (DMARDs). There are currently 3 classes of biological agents that are approved for the treatment of psoriatic disease: tumor necrosis factor alpha inhibitors (TNFi), including etanercept, infliximab, adalimumab, golimumab, and certolizumab pegol; ustekinumab, a monoclonal antibody (mAb) directed against interleukin (IL)-12 and IL-23; and secukinumab, a human anti-IL-17A mAb. Other agents are in development. Our growing experience with these medications has revolutionized the approach to disease management in PsA. AREAS COVERED: This article discusses the rationale for using biological therapies in PsA, highlighting clinical trial evidence that supports the use of these agents. We summarize novel treatment approaches using biological therapies in the management of PsA, including early intervention, targeted therapy, TNFi switching, combination therapy, and tapering or discontinuation of biological therapy. We conclude with a discussion of the importance comorbidities have on selection of therapy. EXPERT OPINION: The advent of highly effective biological therapies has revolutionized the management of patients with PsA. Growing experience with these agents has led to novel treatment approaches that may improve clinical outcomes for PsA patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".