Prevalence of omalizumab-resistant chronic urticaria and real-world effectiveness of dupilumab in patients with omalizumab-refractory chronic urticaria: a single-centre experience
Bibliographic record
Abstract
Chronic urticaria (CU) is characterized by weals (hives) angio-oedema (or both) that last for ≥ 6 weeks, with chronic spontaneous urticaria (CSU) being the most common subtype. Patients with omalizumab-refractory CSU represent an unmet clinical need. In this study, we aimed to assess the prevalence and predictors of omalizumab failure in a large cohort of patients with CU and assess the effectiveness of dupilumab for omalizumab-refractory CU. Of 338 patients with CU, 33 received omalizumab; 69.7% (n = 23) were responders and 30.3% (n = 10) were nonresponders. Bivariate regression demonstrated that female sex [adjusted odds ratio (aOR) 1.53, 95% confidence interval (CI) 1.14-2.06], higher baseline weekly urticaria activity score (aOR 1.05, 95% CI 1.01-1.09) and older age (controlling for sex) (aOR 1.00, 95% CI 1.00-1.01) were associated with omalizumab failure. Of 10 patients with omalizumab-refractory CU, 3 were well controlled with ciclosporin (all children), whereas the 7 adults failed a mean [standard deviation (SD)] of 5.6 (2.6) treatments, including ciclosporin. All seven achieved a complete response with dupilumab, with time to response varying between 1 and 6 months. While our results suggest a favourable efficacy of dupilumab in patients with omalizumab-refractory CU, future confirmatory studies are required.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".