The clinical relevance of dupilumab serum concentration in patients with atopic dermatitis: a two-center prospective cohort study
Bibliographic record
Abstract
Background Dupilumab is prescribed in one dosage across adult atopic dermatitis patients. Differences in drug exposure may explain variation in treatment response.Objective Investigating the clinical relevance of dupilumab serum concentration in atopic dermatitis in real-world practice.Methods In two centres (Netherlands, UK), adults treated with dupilumab for atopic dermatitis were evaluated for effectiveness and safety pre-treatment and at 2, 12, 24 and 48 weeks; trough serum samples were analysed for dupilumab concentration at corresponding time points.Results In 149 patients, median dupilumab levels during follow-up ranged from 57.4-72.4μg/mL. Levels showed high inter-patient and low intra-patient variability. No correlation was found between levels and ΔEASI. At 2 weeks, levels of ≥64.1μg/mL predict EASI ≤ 7 at 24 weeks (specificity:100%, sensitivity:60%;p = 0.022). At 12 weeks, ≤32.7μg/mL predicts EASI > 7 at 24 weeks (sensitivity:95%, specificity:26%;p = 0.011). Inverse correlations were found between baseline EASI and levels at 2, 12 and 24 weeks (r=-0.25-0.36;p ≤ 0.023). Low levels were particularly observed in patients with adverse events, treatment interval deviation and discontinuation.Conclusion At the on-label dosage, the measured range of dupilumab levels does not seem to yield differences in treatment effectiveness. However, disease activity does seem to influence dupilumab levels - higher baseline disease activity results in lower levels at follow-up.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".