Pharmacologic treatment of eosinophilic esophagitis: efficacious, likely efficacious, and failed drugs
Bibliographic record
Abstract
Background: Treatment options for Eosinophilic esophagitis (EoE) evolve rapidly. This review focuses on pharmacologic options to treat EoE. Summary: Orodisopersible budenoside tablets (Jorveza®) have been approved by regulatory authorities for EoE treatment of adults in Europe, Canada and Australia, but not the United States. Jorveza®, as compared to placebo, is effective in inducing and maintaining histologic and clinical remission over time. Before the approval of Jorveza®, several investigator-initiated randomized controlled clinical studies evaluated esophagus-targeted formulations of either budesonide or fluticasone to treat pediatric and adult EoE patients. These drugs were generally efficacious in inducing and maintaining histological and clinical remission. Proton-pump inhibitors (PPI) are used off-label for EoE treatment of pediatric and adult EoE patients given that they are able to induce histologic and clinical remission. Dupilumab (Dupixent®), a monoclonal antibody targeted against IL-4 and IL-13, was approved by regulatory authorities in the United States, Europe, Canada, but not yet Australia. In Europe, including Switzerland, Dupixent® is approved to treat EoE patients of at least 12 years of age with at least 40 kg body weight if they are either unresponsive or intolerant to or not candidates for conventional EoE therapies. Due to lack of efficacy or unfavorable safety profile, the following drugs are not recommended for EoE treatment: systemic steroids, sodium cromoglycate, montelukast, azathioprine, TNF-antagonists (eg. infliximab), vedolizumab (mAb against α4β7), benralizumab (mAb against IL-5 receptor), mepolizumab (mAb against IL-5), reslizumab (mAb against IL-5), omalizumab (mAb against IgE), and lirentelimab (mAb against siglec-8). Key messages: Long-term effectiveness and safety data on different drugs are currently sparse. Concerted efforts of different stakeholders will be necessary to continue the endeavour of providing our patients with much-needed therapies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".