A systematic review of recent randomized controlled trials for palmoplantar pustulosis
Bibliographic record
Abstract
Palmoplantar pustulosis (PPP) is a chronic inflammatory condition, that leads to significant functional impairment and reduced quality of life. Despite its low incidence, treatment options are diverse and often ineffective, necessitating a review of recent therapeutic advances. This review aims to evaluate the efficacy and safety of recent therapeutic options for the treatment of PPP, focusing on phototherapy, systemic therapies, and biologics. A systematic literature search identified 13 studies evaluating phototherapy and systemic therapies, including biologics. Inclusion criteria focused on randomized controlled trials with participants diagnosed with PPP. Phototherapy showed success: excimer laser demonstrated high efficacy for severe disease [PPP Area and Severity Index (PPPASI)-75 of 95.0%], while psoralen plus ultraviolet A therapy with retinoids or fumaric acid esters worked well in milder disease (PPPASI-90 of 90.0 and 81.8%, respectively). Evidence supports the efficacy and safety of guselkumab, brodalumab, and apremilast over a range of disease severity (PPPASI-50 ranged from 57.4 to 78.3% at week 16). Agents including anakinra, secukinumab, spesolimab, and RIST4721 (primary outcomes not achieved) may not be first-line treatments. By targeting multiple inflammatory pathways in PPP, JAK inhibitors may be more effective than biologics in treating PPP; however, more research is needed to confirm their safety and appropriate use. Multiple new treatments exist for PPP with promising results, however longer-term studies with standardized outcome reporting are needed to determine optimal treatment strategies and their comparative efficacy.
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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 | 0.012 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.013 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".