Treatment of Psoriasis in Patients With Psoriatic Arthritis: An Updated Literature Review Informing the 2021 GRAPPA Treatment Recommendations
Bibliographic record
Abstract
OBJECTIVE: Our aim was to summarize and evaluate the current quality of evidence regarding the efficacy of therapies for cutaneous psoriasis (PsO) in patients with psoriatic arthritis (PsA). METHODS: A literature search of MEDLINE, Embase, Cochrane Library databases, and conference abstracts was conducted to identify interventional randomized controlled trials in patients with PsA between February 2013 and December 2021. Studies were included if PsO outcomes included achieving at least 75% improvement in the Psoriasis Area and Severity Index and the blinded comparison period was ≥ 10 weeks. The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology was employed to assess quality of the evidence to inform and update the 2021 Group for Research and Assessment of Psoriasis and Psoriatic Arthritis (GRAPPA) treatment recommendations. RESULTS: A total of 116 studies and 36 abstracts identified in the initial search were screened. A total of 37 studies (40 treatment arms) met the criteria for final inclusion. Phosphodiesterase 4 inhibitors, Janus kinase inhibitors, and tyrosine kinase 2 inhibitors, interleukin 17 inhibitors (IL-17i), IL-12/23i, IL-23i, and tumor necrosis factor inhibitors (TNFi) had high-quality data broadly supporting the efficacy of each class for plaque PsO over placebo. Head-to-head studies with high-quality data supported both IL-17i and IL-23i over TNFi. CONCLUSION: Several pharmacologic therapeutic classes have high-quality evidence demonstrating efficacy for cutaneous PsO in the PsA population. The findings will be integrated into the 2021 GRAPPA treatment recommendations, intended to guide selection of a therapeutic class where efficacy in 1 or more cutaneous or musculoskeletal domains is required.
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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 | 0.013 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".