Glucagon-Like Peptide 1 Receptor Agonists in Patients With Inflammatory Arthritis or Psoriasis
Bibliographic record
Abstract
ABSTRACT: Obesity is a proinflammatory state associated with increased disease severity in various types of inflammatory arthritis. Weight loss is associated with improved disease activity in certain forms of inflammatory arthritis such as rheumatoid arthritis (RA) and psoriatic arthritis (PsA). We conducted a scoping review summarizing the literature evaluating the effect of glucagon-like peptide 1 (GLP-1) receptor agonists on weight and disease activity in patients with inflammatory arthritis or psoriasis. MEDLINE, PubMed, Scopus, and Embase were searched for publications evaluating the role of GLP-1 analogs in RA, PsA, psoriasis, axial spondyloarthritis, systemic lupus erythematosus, systemic sclerosis, gout, and calcium pyrophosphate deposition disease. Nineteen studies were included: 1 gout study, 5 RA studies (3 basic science, 1 case report, and 1 longitudinal cohort), and 13 psoriasis studies (2 basic science, 4 case reports, 2 combined basic science/clinical studies, 3 longitudinal cohorts, and 2 randomized controlled trials). No psoriasis study reported on PsA outcomes. Basic science experiments demonstrated weight-independent immunomodulatory effects of GLP-1 analogs through inhibition of the NF-κB pathway (via AMP-activated protein kinase phosphorylation in psoriasis and prevention of IκBα phosphorylation in RA). In RA, improved disease activity was reported. In psoriasis, 4 of 5 clinical studies demonstrated significant improvements in Psoriasis Area Severity Index and weight/body mass index with no major adverse events. Common limitations included small sample sizes, short follow-up periods, and lack of control groups. GLP-1 analogs safely cause weight loss and have potential weight-independent anti-inflammatory effects. Their role as an adjunct in patients with inflammatory arthritis and obesity or diabetes is understudied, warranting future research.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".