Tofacitinib for the treatment of psoriasis and psoriatic arthritis
Bibliographic record
Abstract
INTRODUCTION: Tofacitinib is a novel oral janus kinase (JAK) inhibitor approved for the treatment of psoriatic arthritis. It was also investigated for the treatment of plaque psoriasis, although it is not approved by the Food and Drug Administration for this indication. This article aimed to summarize the efficacy and safety data of tofacitinib for treatment of psoriatic disease. EVIDENCE ACQUISITION: A comprehensive review of literature was conducted on the PubMed database using the search terms: "((tofacitinib) AND (psoriasis)) OR ((tofacitinib) AND (psoriatic arthritis))". Data from the pivotal clinical trials evaluating tofacitinib in the treatment of psoriatic disease were summarized. EVIDENCE SYNTHESIS: The Oral-treatment Psoriasis Trial (OPT) study series demonstrated that tofacitinib is efficacious in the treatment of plaque psoriasis with an acceptable safety profile. The OPT studies also demonstrated the non-inferiority of tofacitinib 10 mg twice daily compared to etanercept. The Oral Psoriatic Arthritis Trial (OPAL) study series demonstrated that tofacitinib significantly improved psoriatic arthritis outcomes compared to placebo and had an acceptable safety profile. Its efficacy is comparable to adalimumab in psoriatic arthritis. CONCLUSIONS: Patients treated with tofacitinib should be monitored for herpes zoster, malignancies, blood clots, and changes in laboratory values. Overall, tofacitinib is a useful new systemic agent in the treatment of psoriatic disease. Its oral route of administration, novel JAK pathway target, short half-life, and strong recapture rates after treatment interruption make it a unique new tool for psoriatic disease management. Further long-term studies will help determine its role in the treatment algorithm for psoriatic arthritis and its indication for plaque psoriasis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| 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) | 0.017 | 0.003 |
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".