Cardiometabolic Effects of Apremilast in Patients With Psoriatic Arthritis: A Prospective Cohort Study
Bibliographic record
Abstract
Objective Psoriatic arthritis (PsA) is associated with metabolic and cardiovascular (CV) disease. Studies have suggested that treatment with apremilast is associated with weight loss and other cardiometabolic benefits. This study aimed to examine the effects of apremilast on body weight, body composition, and CV risk factors in patients with PsA. Methods This longitudinal, nonrandomized, multicenter trial included adults with active PsA initiating apremilast (30 mg twice daily after a step-up regimen). Patients were followed for 12 months, and measurements were done at baseline and repeated at weeks 26 and 52. Body composition, the primary outcome, was assessed using dual-energy x-ray absorptiometry. Secondary outcomes included disease activity (Disease Activity Score in 28 joints [DAS28] based on C-reactive protein [CRP]), blood pressure (BP), lipids, intima-media thickness, and glucose. Statistical analysis involved mixed models adjusted for relevant covariates. Results Forty-four patients were included, with a mean age of 56 (SD 11) years and a median BMI (kg/m2) of 28 (IQR 24-33). A total of 17 patients completed the study, whereas 27 discontinued due to ineffectiveness or side effects. After 1 year of apremilast, significant reductions were observed in multiple body mass measures, including total fat (–7.4 kg;P= 0.005) and android fat (–1.1 kg;P= 0.002). Lean mass remained stable. BP showed minor reduction, whereas lipids, intima-media thickness, and glucose levels did not change. Disease activity improved, with a significant decrease in DAS28-CRP (–0.6;P= 0.01). Android fat correlated most strongly with disease activity reduction (r0.31;P= 0.004). Conclusion This study demonstrates that apremilast reduces fat mass in patients with PsA and suggests beneficial CV and metabolic effects, potentially reducing the risk of CV events.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".