Biologic Therapy for Psoriatic Arthritis or Moderate to Severe Plaque Psoriasis: Systematic Review with Pairwise and Network Meta-Analysis
Bibliographic record
Abstract
Background: A comprehensive assessment of the risk-benefit profile of biologic agents in psoriasis is lacking. We conducted a network meta-analysis of randomized trials on biologic agents in psoriasis. Methods: Trials on biologic agents in psoriasis (including psoriatic arthritis) were sought in several databases. Endpoints were ≥75% Reduction in the Psoriasis Area and Severity Index (PASI75), ≥20% improvement in the American College of Rheumatology core set of outcomes (ACR20), serious adverse events (SAE), and adverse events (AE) at the longest available non-cross-over follow-up. Random-effect methods were used to obtain pairwise and network pooled estimates. Results: A total of 52 trials with 17,617 patients and 9 different biologic agents included, with 52% affected by psoriatic arthritis. After an average follow-up of 18 weeks, treatment with placebo was associated with a 5.9% (5.2%-6.6%) rate of PASI75, 17.4% (15.1%-19.6%) of ACR20, 2.4% (1.9%-2.8%) of SAE, and 51.8% (50.2%-53.4%) of AE. Several biologic agents provided higher PASI75 rates than placebo, with golimumab yielding the most favorable results (relative risk [RR]=14.02 [6.85-17.11]). Accordingly, several agents provided higher ACR20 rates than placebo, with infliximab yielding the most favorable results (RR=3.02 [1.67-4.55]). Overall, rates of SAE and AE were higher for several but not all biologic agents versus placebo, with golimumab being associated with the most favorable results for SAE (RR=0.40 [0.11-1.41]), and abatacept for AE (RR=1.00 [0.79-1.22]). Conclusions: Efficacy and safety of biologic agents for psoriasis differ, and clinicians should bear in mind these features to maximize safety and efficacy in the individual patient.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".