Efficacy and safety of guselkumab, an anti-interleukin-23 monoclonal antibody, compared with adalimumab for the continuous treatment of patients with moderate to severe psoriasis: Results from the phase III, double-blinded, placebo- and active comparator–controlled VOYAGE 1 trial
Bibliographic record
Abstract
BACKGROUND: Guselkumab, an interleukin-23 blocker, was superior to adalimumab in treating moderate to severe psoriasis in a phase II trial. OBJECTIVES: We sought to compare efficacy and safety of guselkumab with adalimumab and placebo in patients with psoriasis treated for 1 year. METHODS: Patients were randomized to guselkumab 100 mg (weeks 0 and 4, then every 8 weeks; n = 329); placebo→guselkumab (weeks 0, 4, and 12 then guselkumab at weeks 16 and 20, then every 8 weeks; n = 174); or adalimumab (80 mg week 0, 40 mg week 1, then 40 mg every 2 weeks through week 47; n = 334). Physician-reported outcomes (Investigator Global Assessment, Psoriasis Area and Severity Index [PASI]), patient-reported outcomes (Dermatology Life Quality Index, Psoriasis Symptoms and Signs Diary), and safety were evaluated through week 48. RESULTS: Guselkumab was superior (P < .001) to placebo at week 16 (85.1% vs 6.9% [Investigator Global Assessment score of 0/1 (cleared/minimal)] and 73.3% vs 2.9% [90% or greater improvement in PASI score from baseline (PASI 90)]). Guselkumab was also superior (P < .001) to adalimumab for Investigator Global Assessment 0/1 and PASI 90 at week 16 (85.1% vs 65.9% and 73.3% vs 49.7%), week 24 (84.2% vs 61.7% and 80.2% vs 53.0%), and week 48 (80.5% vs 55.4% and 76.3% vs 47.9%). Furthermore, guselkumab significantly improved patient-reported outcomes through week 48. Adverse event rates were comparable between treatments. LIMITATIONS: Analyses were limited to 48 weeks. CONCLUSIONS: Guselkumab demonstrated superior efficacy compared with adalimumab and was well tolerated in patients with psoriasis through 1 year.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| 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".