Guselkumab Reduces Disease- and Mechanism-Related Biomarkers More Than Adalimumab in Patients with Psoriasis: A VOYAGE 1 Substudy
Bibliographic record
Abstract
Background Psoriasis is an immune-mediated inflammatory disease characterized by activation of interleukin (IL)-23–driven IL-17–producing T cell and other IL-23 receptor+ IL-17–producing cell responses. Selective blockade of IL-23p19 with guselkumab was superior to blockade of tumor necrosis factor-α (TNF-α) with adalimumab in treating moderate-to-severe psoriasis. Objective Pharmacodynamic (PD) responses of guselkumab versus adalimumab were compared in patients with psoriasis in VOYAGE 1. Design Inflammatory cytokine serum levels were assessed (n=118) and lesional and nonlesional skin biopsies were collected (n=38) in patient subsets at baseline, 4/24/48-weeks post-treatment to evaluate PD responses of guselkumab versus adalimumab. Results Guselkumab provided rapid reductions in serum IL-17A, IL-17F, and IL-22 levels by Week 4 versus baseline that were maintained through Weeks 24 and 48 (p<0.001). The magnitude of reduction of IL-17A and IL-22 at Week 48, and IL-17F at Weeks 4/24/48 were greater with guselkumab versus adalimumab (all p<0.05). In skin, guselkumab reduced expression of IL-23/IL-17 pathway-associated and psoriasis-associated genes. Conclusion These data provide extensive characterization of PD anti-inflammatory responses to IL-23p19 and TNF-α inhibition in human blood and tissue over time with clinically approved doses of guselkumab and adalimumab.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".