Development of a core outcome set for therapeutic studies in eosinophilic esophagitis (COREOS)
Bibliographic record
Abstract
BACKGROUND: End points used to determine treatment efficacy in eosinophilic esophagitis (EoE) have evolved over time. With multiple novel therapies in development for EoE, harmonization of outcomes measures will facilitate evidence synthesis and appraisal when comparing different treatments. OBJECTIVE: We sought to develop a core outcome set (COS) for controlled and observational studies of pharmacologic and diet interventions in adult and pediatric patients with EoE. METHODS: Candidate outcomes were generated from systematic literature reviews and patient engagement interviews and surveys. Consensus was established using an iterative Delphi process, with items voted on using a 9-point Likert scale and with feedback from other participants to allow score refinement. Consensus meetings were held to ratify the outcome domains of importance and the core outcome measures. Stakeholders were recruited internationally and included adult and pediatric gastroenterologists, allergists, dieticians, pathologists, psychologists, researchers, and methodologists. RESULTS: The COS consists of 4 outcome domains for controlled and observational studies: histopathology, endoscopy, patient-reported symptoms, and EoE-specific quality of life. A total of 69 stakeholders (response rate 95.8%) prioritized 42 outcomes in a 2-round Delphi process, and the final ratification meeting generated consensus on 33 outcome measures. These included measurement of the peak eosinophil count, Eosinophilic Esophagitis Histology Scoring System, Eosinophilic Esophagitis Endoscopic Reference Score, and patient-reported measures of dysphagia and quality of life. CONCLUSIONS: This interdisciplinary collaboration involving global stakeholders has produced a COS that can be applied to adult and pediatric studies of pharmacologic and diet therapies for EoE and will facilitate meaningful treatment comparisons and improve the quality of data synthesis.
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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 | 0.343 | 0.397 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.014 |
| Bibliometrics | 0.020 | 0.011 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.003 | 0.004 |
| 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".