Efficacy of Systemic Treatments for Moderate to Severe Plaque Psoriasis: Systematic Review and Meta-Analysis
Bibliographic record
Abstract
AIMS: To compare the efficacy of psoriasis treatments through a systematic literature review and meta-analysis. METHODS: Randomized controlled trials evaluating the Psoriasis Area and Severity Index (PASI) were identified and assessed for quality. PASI responses were modeled using a mixed-treatment comparison, which enabled the estimation of the relative effectiveness of several treatments. Sensitivity analyses were performed. RESULTS: Twenty-two trials were included. Tumor necrosis factor (TNF) inhibitors were most likely to achieve PASI 75, with a mean relative risk (RR) of 15.57 (95% CI 12.46-19.25) versus mean RRs of 9.24 (95% CI 5.33-13.91) for systemic and 5.65 (95% CI 3.74-7.97) for T-cell therapies. Infliximab (81%) and adalimumab (71%) had greater probabilities of achieving PASI 75 than etanercept (50%). Dosage was an important determinant of outcome. CONCLUSIONS: TNF inhibitors were more effective than T cell agents; adalimumab and infliximab were more effective than systemic therapies and etanercept. Evidence-based comparisons support patient and physician decisions.
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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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".