Evidence Gaps in Clinical Trials of Pharmacologic Treatment for H1-Antihistamine-Refractory Chronic Spontaneous Urticaria: A Systematic Review and Future Perspectives
Bibliographic record
Abstract
No data addressing issues concerning disparities in participant and trial characteristics and trial outcome reporting have been established in clinical trials for H1-antihistamine-refractory chronic spontaneous urticaria (CSU). To better harmonize and compare the different treatment interventions, we systematically evaluated the overall landscape of pharmacological treatments for H1-antihistamine-refractory CSU clinical trials published between 2000 and 2021. This systematic review included 23 randomized clinical trials involving 2480 participants from 22 countries. We found significant increases in the number of globally published and newly tested drugs, especially biologic drugs. Regarding relatively small trials, we found that people living with H1-antihistamine-refractory CSU who were identified as members of minority groups (non-white population), populations of regions other than North America/Europe, and populations of low- to lower/upper-middle-income countries are underrepresented. Most trials were designed to evaluate treatment efficacy and safety profiles; however, less than half of the included trials reported the patient's perspective in terms of patient-reported outcomes. Disparities in outcome reporting, including clinimetric tools for assessing treatment response and outcome sets, were observed. To close the evidence gap in H1-antihistamine-refractory CSU trials, strategies for improving trial and participant enrollment and standardizing core outcome sets for trial reporting are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 teacher head, 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".