S1074 A Prospective Approach to Disease Progression, Treatment Response and Quality of Life in Eosinophilic Esophagitis From Canada
Bibliographic record
Abstract
Introduction: Eosinophilic esophagitis (EoE) is a chronic, immune-mediated disease marked by esophageal dysfunction and eosinophil-predominant inflammation in the esophagus. Available treatments include proton pump inhibitors, topical corticosteroids, diet, biologics, and esophageal dilation. However, optimal long-term strategies and their durability remain unclear. EoE also significantly impacts quality of life (QoL) due to dietary restrictions, fear of food impaction, and healthcare utilization. This study explores disease progression, treatment response, and patient-reported outcomes (PROs) in EoE patients from a Canadian clinic. Methods: This prospective cohort study included 60 patients diagnosed with EoE between 2011 and 2025. Data was collected on demographics, treatments, histology, Eosinophilic Esophagitis Endoscopic Reference Score (EREFS), and Adult Eosinophilic Esophagitis Quality of Life (EoE-QOL-A) questionnaire scores. Wilcoxon signed-rank, Spearman correlation, and ANOVA were used to assess changes from initial consult to follow-up. Results: Among 60 patients (76.7% men, median age 30.4 years [interquartile range (IQR) 17.8-36.2]), median disease duration was 6.2 years [IQR 4.4-9.7]. Only 3% did not have a follow-up within 12 months of first assessment. Patients tried an average of 2.28 treatment classes. Eosinophil counts declined from 50 to 11/hpf (P < 0.0001) and EREFS scores improved from 3.0 to 2.0 (P = 0.0002) with treatment. QoL scores improved from 43 to 24 (P < 0.0001) with treatment, including all subscores. History of food bolus impaction did not significantly correlate with poorer QoL (P = 0.1684 at baseline, P = 0.0918 at follow-up). Changes in eosinophil counts and EREFS were not correlated with QoL (ρ = 0.14 and -0.20, P > 0.1). ANOVA showed no significant differences by treatment group for change in eosinophils (P = 0.398), EREFS (P = 0.99), or QoL scores (P = 0.185). Conclusion: While significant improvements were seen in eosinophils, EREFS, and QoL over time, no statistical differences were found based on treatment type. This likely reflects small sample size effect. Combination therapies were frequently used in real-world practice prior to the approval of monoclonal antibodies. The lack of correlation between eosinophil counts, EREFS, and QoL demonstrate the complex interplay between objective disease control and patient experiences. The observed improvements in QoL scores with treatment highlight the importance of including PROs in longitudinal care and future trials.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".