Efficacy and safety of mirikizumab ( <scp>LY</scp> 3074828) in the treatment of moderate‐to‐severe plaque psoriasis: results from a randomized phase <scp>II</scp> study
Bibliographic record
Abstract
BACKGROUND: Inhibiting interleukin (IL)-23 in patients with psoriasis has demonstrated high levels of skin clearance. OBJECTIVES: To investigate, in a phase II (AMAF; NCT02899988), multicentre, double-blind trial, the efficacy and safety of three doses of mirikizumab (LY3074828), a p19-directed IL-23 antibody, vs. placebo in patients with moderate-to-severe plaque psoriasis. METHODS: Adult patients were randomized 1 : 1 : 1 : 1 to receive placebo (n = 52), mirikizumab 30 mg (n = 51), mirikizumab 100 mg (n = 51) or mirikizumab 300 mg (n = 51) subcutaneously at weeks 0 and 8. The primary objective was to evaluate the superiority of mirikizumab over placebo in achieving a 90% improvement in the Psoriasis Area and Severity Index (PASI 90) response at week 16. Comparisons were done using logistic regression analysis with treatment, geographical region and previous biological therapy in the model. Missing data were imputed as nonresponses. RESULTS: Ninety-seven per cent of patients completed the first 16 weeks of the study. The primary end point was met for all mirikizumab dose groups vs. placebo, with PASI 90 response rates at week 16 of 0%, 29% (P = 0·009), 59% (P < 0·001) and 67% (P < 0·001) for patients receiving placebo, and mirikizumab 30 mg, 100 mg and 300 mg, respectively. There were two (1%) serious adverse events in mirikizumab-treated patients vs. one (2%) in a placebo-group patient. CONCLUSIONS: At week 16, 67% of patients treated with mirikizumab 300 mg at 8-week intervals achieved PASI 90. The percentage of patients reporting at least one treatment-emergent adverse event was similar among patients treated with placebo or mirikizumab.
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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 | 0.002 |
| 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 | 0.001 | 0.002 |
| 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".