Objective: Eosinophilic esophagitis (EoE) is an emerging pediatric disease that can significantly impact patients’ quality of life. Endoscopy with biopsy sampling and histopathological analysis is the gold standard for diagnosing and monitoring EoE. However, its invasive nature, high cost, and potential complications pose significant concerns. This study aims to assess the predictive power of a combined model incorporating cellular indices and the presence of food allergies for screening EoE in children with dysphagia.
Methods: This diagnostic study included pediatric patients (0–15 years) who underwent esophagogastroduodenoscopy due to suspected EoE between 2015 and 2022. Patients were classified into two groups: those with normal histology and those diagnosed with EoE. Logistic regression models were used to compare food allergy history (FAH), peripheral blood eosinophil counts, and various cellular indices, including the eosinophil-to-lymphocyte ratio (ELR) and eosinophil-to-neutrophil ratio (ENR). These indices were calculated as the ratio of the respective cell counts and transformed into binary variables based on their optimal cutoff points determined using Youden’s index. Predictive models incorporating different combinations of these variables were developed to assess their sensitivity, specificity, and predictive values for EoE screening. Internal validation was performed using bootstrap techniques (n=1,000). Consent was obtained from the Institutional Review Board.
Results: A total of 24 patients with EoE and 17 with normal histology were included. The best predictive model for EoE included FAH, ELR, and ENR, yielding an AUC of 0.864 (corrected AUC: 0.835), a sensitivity of 79%, and a specificity of 78%. The positive predictive value was 83%, while the negative predictive value was 72%.
Conclusions: The combination of eosinophilic cellular indices (ELR, ENR) and food allergy history could serve as a useful screening tool for children with dysphagia, potentially reducing unnecessary invasive procedures in patients with a low likelihood of EoE.
Keywords: Eosinophilic esophagitis, dysphagia, biomarker
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