Efficacy and safety of ixekizumab for the treatment of moderate-to-severe plaque psoriasis: Results through 108 weeks of a randomized, controlled phase 3 clinical trial (UNCOVER-3)
Bibliographic record
Abstract
BACKGROUND: Ixekizumab, a high-affinity monoclonal antibody that selectively targets interleukin 17A, is efficacious in treating moderate-to-severe plaque psoriasis through 60 weeks. OBJECTIVE: To evaluate the efficacy and safety of ixekizumab through 108 weeks of treatment in UNCOVER-3. METHODS: Patients (N = 1346) were randomized 2:2:2:1 to 80 mg ixekizumab every 2 or 4 weeks, 50 mg etanercept twice weekly, or placebo. At week 12, patients switched to ixekizumab every 4 weeks during a long-term extension (LTE) period. Efficacy data were summarized using as-observed, multiple imputation (MI), and modified MI (mMI) methods. RESULTS: For patients (N = 385) receiving the recommended dose (ixekizumab every 2 weeks on weeks 0-12 and every 4 weeks during LTE), the 108-week as-observed, MI, and mMI response rates were 93.4%, 88.3%, and 83.6%, respectively, for patients achieving ≥75% improvement from baseline in the Psoriasis Area and Severity Index, and the 108-week as-observed, MI, and mMI response rates were 82.6%, 78.3%, and 74.1%, respectively, for patients with a static Physician's Global Assessment score of 0 or 1. During LTE, 1077 (84.5%) patients reported ≥1 treatment-emergent adverse event, and 85% were mild or moderate in severity. Discontinuation because of adverse events occurred in 6.4% of patients. LIMITATIONS: There was no comparison treatment group after week 12. CONCLUSION: Ixekizumab is well tolerated and demonstrates persistent efficacy through 108 weeks.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".