Efficacy and safety of tildrakizumab for the treatment of moderate-to-severe plaque psoriasis of the scalp: A multicenter, randomized, double-blind, placebo-controlled, Phase 3b study
Bibliographic record
Abstract
BACKGROUND: Scalp psoriasis is common and difficult to treat. OBJECTIVE: To evaluate efficacy and safety of tildrakizumab for the treatment of scalp psoriasis. METHODS: In this Phase 3b, randomized, double-blind, placebo (PBO)-controlled study (NCT03897088), patients with moderate-to-severe plaque psoriasis affecting the scalp (Investigator Global Assessment modified [IGA mod] 2011 [scalp] ≥3, Psoriasis Scalp Severity Index [PSSI] ≥12, ≥30% scalp surface area affected) received tildrakizumab 100 mg or PBO at W0 and W4. The primary endpoint was IGA mod 2011 (scalp) score of "clear" or "almost clear" with ≥2-point reduction from baseline at W16 (IGA mod 2011 [scalp] response). Key secondary endpoints were PSSI 90 response at W12 and W16 and IGA mod 2011 (scalp) response at W12. Safety was assessed from adverse events. RESULTS: Of patients treated with tildrakizumab (n = 89) vs PBO (n = 82), 49.4% vs 7.3% achieved IGA mod 2011 (scalp) response at W16 (primary endpoint) and 46.1% vs 4.9% at W12; 60.7% vs 4.9% achieved PSSI 90 response at W16 and 48.3% vs 2.4% at W12 (all P < .00001). No serious treatment-related adverse events occurred. LIMITATIONS: Only short-term data are presented. CONCLUSION: Tildrakizumab was efficacious for the treatment of scalp psoriasis with no new safety signals.
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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 | 0.003 | 0.001 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".