Evan S Dellon1,2, Spencer Rusin3, Jessica H Gebhart1, Shannon Covey3, Olga Speck3, Kimberly Woodward3, Leana L Higgins1, RoseMary Beitia1, Ryan D Madanick1,2, Sidney Levinson1,2, John T Woosley3, Nicholas J Shaheen1,2. 1. Center for Esophageal Diseases and Swallowing, Division of Gastroenterology and Hepatology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA. 2. Center for Gastrointestinal Biology and Disease, Division of Gastroenterology and Hepatology, Department of Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA. 3. Department of Pathology and Laboratory Medicine, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA.
Abstract
OBJECTIVES: Eosinophilic esophagitis (EoE) is difficult to distinguish from gastroesophageal reflux (GERD) and other causes of dysphagia. We assessed the utility of a set of clinical and endoscopic features for predicting EoE without obtaining esophageal biopsies. METHODS: We prospectively enrolled consecutive adults undergoing outpatient upper endoscopy at the University of North Carolina from July 2011 through December 2013. Incident cases of EoE were diagnosed per consensus guidelines. Non-EoE controls had either GERD- or dysphagia-predominant symptoms. A predictive model containing clinical and endoscopic, but no histological, data was assessed. Receiver operator characteristic curves were constructed and the area under the curve (AUC) was calculated. RESULTS: A total of 81 EoE cases (mean age 38 years; 60% male; 93% white; 141 eosinophils per high-power field (eos/hpf)) and 144 controls (mean age 52, 38% male; 82% white; 3 eos/hpf) were enrolled. A combination of clinical (age, sex, dysphagia, food allergy) and endoscopic (rings, furrows, plaques, hiatal hernia) features was highly predictive of EoE. The AUC was 0.944, with sensitivity, specificity, and accuracy of 84, 97, and 92%. Similar values were seen after limiting controls to those with only reflux or dysphagia or to those with esophageal eosinophilia not due to EoE. CONCLUSIONS: We validated a set of clinical and endoscopic features to predict EoE with a high degree of accuracy and allow identification of those at very low risk of disease. Use of these predictors at the point-of-care will avoid the effort and expense of low-yield histological examinations for EoE.
OBJECTIVES:Eosinophilic esophagitis (EoE) is difficult to distinguish from gastroesophageal reflux (GERD) and other causes of dysphagia. We assessed the utility of a set of clinical and endoscopic features for predicting EoE without obtaining esophageal biopsies. METHODS: We prospectively enrolled consecutive adults undergoing outpatient upper endoscopy at the University of North Carolina from July 2011 through December 2013. Incident cases of EoE were diagnosed per consensus guidelines. Non-EoE controls had either GERD- or dysphagia-predominant symptoms. A predictive model containing clinical and endoscopic, but no histological, data was assessed. Receiver operator characteristic curves were constructed and the area under the curve (AUC) was calculated. RESULTS: A total of 81 EoE cases (mean age 38 years; 60% male; 93% white; 141 eosinophils per high-power field (eos/hpf)) and 144 controls (mean age 52, 38% male; 82% white; 3 eos/hpf) were enrolled. A combination of clinical (age, sex, dysphagia, food allergy) and endoscopic (rings, furrows, plaques, hiatal hernia) features was highly predictive of EoE. The AUC was 0.944, with sensitivity, specificity, and accuracy of 84, 97, and 92%. Similar values were seen after limiting controls to those with only reflux or dysphagia or to those with esophageal eosinophilia not due to EoE. CONCLUSIONS: We validated a set of clinical and endoscopic features to predict EoE with a high degree of accuracy and allow identification of those at very low risk of disease. Use of these predictors at the point-of-care will avoid the effort and expense of low-yield histological examinations for EoE.
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