Efficacy and Safety of Apremilast Monotherapy for Moderate to Severe Psoriasis: Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Apremilast is a new oral drug for the treatment of moderate to severe plaque psoriasis that reduces inflammation by inhibiting phosphodiesterase 4. Its efficacy and safety data are limited; hence, real-world outcomes are important for elucidating the full spectrum of its adverse events (AEs) and expanding generalizability of clinical trial findings. OBJECTIVE: Assess the efficacy and safety of apremilast monotherapy in real-world practice. METHODS: A retrospective chart review was conducted in 2 academic dermatology practices. Efficacy was measured as the proportion of patients achieving a ≥75% reduction from baseline Psoriasis Area and Severity Index score (PASI-75) or a Psoriasis Global Assessment (PGA) score of 0 (clear) or 1 (almost clear) at 16 weeks. Safety was measured as the proportion of patients reporting ≥1 AE at 16 weeks. RESULTS: Thirty-four patients were included. EFFICACY: 19 patients (55.9%) achieved PASI-75 or PGA 0/1. SAFETY: 23 patients (67.6%) experienced ≥1 AEs. Five patients (14.7%) withdrew treatment prior to week 16 due to AEs. One patient withdrew treatment due to mood lability and depression. Common AEs included headache (32.4%), nausea (20.6%), diarrhoea (14.7%), weight loss (8.8%), and loose stool (8.8%). CONCLUSION: Apremilast monotherapy had higher efficacy with similar safety outcomes in the real world compared to clinical trials. There were higher proportions of reported headaches compared to clinical trials. This study supports the apremilast monotherapy clinical trial findings, suggesting that it has an acceptable safety profile and significantly reduces the severity of moderate to severe plaque psoriasis. Limitations include the retrospective nature of the study.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".