EoE ToT Module 3 References-Dellon et al Clin Gastroenterol Hepatol 2009 Clinical endoscopic histologic findings distinguish EoE from GERD

Dellon et al Clin Gastroenterol Hepatol 2009 Clinical endoscopic histologic findings distinguish EoE from GERD

Pdf Summary

This retrospective case-control study, conducted at the University of North Carolina, aimed to identify clinical, endoscopic, and histologic features that could reliably distinguish Eosinophilic Esophagitis (EoE) from Gastroesophageal Reflux Disease (GERD). Data from 151 patients with EoE and 226 control patients with GERD were analyzed. Key findings that independently predict EoE include younger age, higher incidence of dysphagia, documented food allergies, presence of esophageal rings, linear furrows, white plaques or exudates, absence of a hiatal hernia, higher maximum eosinophil count, and eosinophil degranulation observed in biopsy specimens. This predictive model achieved an area under the receiver operator characteristic (ROC) curve of 0.934, indicating high diagnostic accuracy.<br /><br />The study found that EoE patients were generally younger and more often male compared to those with GERD. Symptomatically, EoE patients exhibited more dysphagia and food impaction, whereas GERD patients reported higher incidences of heartburn and abdominal pain. Endoscopically, EoE patients commonly had findings such as rings, strictures, and linear furrows, whereas GERD patients more frequently had hiatal hernias. Histopathologically, EoE patients had higher eosinophil counts with prominent degranulation and microabscesses, along with diffuse eosinophil distribution.<br /><br />Seasonal variation was also noted, with EoE diagnoses peaking in the summer months. The model's reliability was supported by various statistical tests, and it suggested that focusing on a combination of clinical, endoscopic, and histologic variables provides a more accurate diagnosis than relying on eosinophil counts alone.<br /><br />The study acknowledged limitations including its retrospective nature and potential bias due to missing data, though efforts were made to mitigate these issues. Despite being conducted at a single center, the findings are consistent with existing literature, suggesting that results may be generalizable. The study concludes that after validation, the model could help in achieving more accurate diagnoses of EoE, potentially leading to better management and treatment of patients.

Keywords

Eosinophilic Esophagitis

Gastroesophageal Reflux Disease

clinical features

endoscopic features

histologic features

diagnostic accuracy

eosinophil count

dysphagia

predictive model

seasonal variation