Phase 2 Trial of Deucravacitinib in Psoriatic Arthritis: Biomarkers Associated With Disease Activity, Pharmacodynamics, and Clinical Responses
Bibliographic record
Abstract
OBJECTIVE: Our objective was to evaluate the association of serum biomarkers with baseline psoriatic arthritis (PsA) disease activity, pharmacodynamic effects of deucravacitinib on biomarker levels, and the relationship between biomarkers and clinical responses to deucravacitinib. METHODS: The phase 2 trial (ClinicalTrials.gov identifier: NCT03881059) randomly assigned 203 patients with PsA 1:1:1 to placebo, deucravacitinib at 6 mg once daily (QD), or deucravacitinib at 12 mg QD. Serum biomarkers associated with the interleukin 23 (IL-23) pathway (IL-17A, β-defensin [BD-2], and IL-19), type I interferon pathway, inflammation, and collagen matrix turnover were measured by immunoassay. Clinical responses (≥75% improvement from baseline in the Psoriasis Area and Severity Index [PASI75] and ≥20% improvement from baseline in American College of Rheumatology criteria [ACR20] responses) were measured at week 16. Hematologic variables were also assessed. RESULTS: IL-17A, BD-2, and IL-19 had a modest association with PASI scores (r = 0.4, r = 0.56, and r = 0.5, respectively) at baseline. In deucravacitinib groups, IL-17A, BD-2, IL-19, C-X-C motif ligand 9 (CXCL9), CXCL10, C-reactive protein, matrix metalloproteinase 3, and collagen type 4 degradation marker levels were significantly reduced at week 16 versus baseline (P < 0.01); higher levels of IL-23 pathway-associated biomarkers predicted higher PASI75 and ACR20 response rates in deucravacitinib-treated patients. Significantly higher PASI75 response rates were seen in patients with high baseline IL-17A (odds ratio 15.76) and BD-2 levels (odds ratio 15.41) versus low baseline IL-17A and BD-2 levels. Changes in hematologic variables that are characteristic of JAK inhibition were not observed with deucravacitinib. CONCLUSION: Deucravacitinib significantly impacted biomarkers associated with Tyk2 signaling pathways of key inflammatory cytokines, including IL-23 and type I interferon, and those related to collagen matrix turnover. These biomarkers may predict treatment responses to deucravacitinib.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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".