Disease burden and predictors associated with non-response to antihistamine-based therapy in chronic spontaneous urticaria
Bibliographic record
Abstract
Background: H1-antihistamines (H1AH) are the first-line treatment for chronic spontaneous urticaria (CSU), but 50% of patients have inadequate disease control at standard doses. Objective: To assess the comorbidity burden and healthcare resource utilization (HRU) associated with non-response to H1AH-based treatments; to identify predictors of non-response. Methods: Optum® de-identified Electronic Health Record dataset (2007-2020) was used to identify adult patients with CSU who initiated a H1AH, alone or in combination with other oral non-biologics (index treatment). Based on twelve-month treatment patterns observed after index treatment initiation, patients were categorized as responders (continued index treatment or had only 1 next H1AH treatment without corticosteroids) or non-responders (continued corticosteroids or had 2 or more treatment switches). Patient characteristics and HRU were assessed in the 12 months before (baseline) and ≥12 months after (follow-up) index treatment initiation. Baseline predictors associated with non-response were identified using machine learning. Results: There were 17 062 patients who met inclusion criteria, and 14824 (86.9%) were classified as non-responders. A higher proportion of non-responders had records of CSU-related symptoms, comorbidities, polypharmacy, and certain laboratory tests than responders at baseline. A higher proportion of non-responders than responders visited an allergist or dermatologist during follow-up (59.5% vs 53.0%). Non-responders had a larger increase in hospitalizations (15.7% vs -2.4%) than responders during follow-up vs baseline. Predictors of non-response included index and baseline treatment classes, types of specialists seen, chronic pulmonary disease, depression, and female sex. Conclusion: A large proportion of CSU patients treated with H1AH-based therapies had uncontrolled disease, contributing to increased HRU and patient burden. Non-responders had more comorbidities and HRU at baseline and follow-up, with steep increases in follow-up hospitalizations relative to baseline, highlighting an urgent need for early disease control.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".