Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records.

Background & Aims: Tools that can automatically predict incident esophageal adenocarcinoma (EAC) and gastric cardia adenocarcinoma (GCA) using electronic health records to guide screening decisions are needed.

Methods: The Veterans Health Administration (VHA) Corporate Data Warehouse was accessed to identify Veterans with 1 or more encounters between 2005 and 2018. Patients diagnosed with EAC (n = 8430) or GCA (n = 2965) were identified in the VHA Central Cancer Registry and compared with 10,256,887 controls.

Yield of Repeat Endoscopy for Barrett's Esophagus After Normal Index Endoscopy.

Introduction: Guidelines suggest 1-time screening with esophagogastroduodenoscopy (EGD) for Barrett's esophagus (BE) in individuals at an increased risk of esophageal adenocarcinoma (EAC). We aimed to estimate the yield of repeat EGD performed at prolonged intervals after a normal index EGD.

Methods: We conducted a national retrospective analysis within the U S Veterans Health Administration, identifying patients with a normal index EGD between 2003 and 2009 who subsequently had a repeat EGD.