Super‐response to guselkumab treatment in patients with moderate‐to‐severe psoriasis: age, body weight, baseline Psoriasis Area and Severity Index, and baseline Investigator's Global Assessment scores predict complete skin clearance
Bibliographic record
Abstract
BACKGROUND: Psoriasis is a chronic immune-mediated inflammatory skin disease that often leads to a diminished quality of life. Goals of treating patients with psoriasis have shifted with more focus on achieving near or complete clearance of the skin. Guselkumab, a fully human monoclonal antibody targeting interleukin-23, is effective in treating moderate-to-severe psoriasis. OBJECTIVE: To describe the baseline characteristics of patients with moderate-to-severe psoriasis achieving super-response (Psoriasis Area and Severity Index [PASI] 100 response at Weeks 20 and 28) after commencing guselkumab treatment. METHODS: Pooled data from VOYAGE 1 and VOYAGE 2 studies identified super-response; baseline demographic, disease and pharmacokinetic characteristics were compared with non-super-response. A stepwise logistic regression analysis identified which factors were potentially predictive of super-response status, with significance level of 0.1. RESULTS: A subset of patients randomized to guselkumab comprised this post hoc analysis (n = 664); 271 patients achieved super-response vs. 393 with non-super-response. Patient age at study entry and baseline body weight (≤90 kg vs. >90 kg), PASI, and Investigator's Global Assessment (IGA) score were significant predictors of super-response status, with odds ratios (95% confidence intervals) of 0.98 (0.967-0.993; P = 0.003), 1.42 (1.026-1.977; P = 0.034), 0.97 (0.955-0.993; P = 0.007) and 0.66 (0.433-0.997; P = 0.048), respectively. More patients with super-response achieved an early response: Week 2 PASI 75 (5.5% vs. 1.8%) and Week 8 PASI 100 (22.5% vs. 3.3%) vs. non-super-response. Median serum guselkumab concentrations through Week 28 were slightly greater in patients with super-response vs. non-super-response. CONCLUSION: Guselkumab was more likely to achieve early clinical responses (complete skin clearance) in younger patients, less obese patients and patients with less severe psoriasis.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".