ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2016
Predicting Barrett's Esophagus in Families: An Esophagus Translational Research Network (BETRNet) Model Fitting Clinical Data to a Familial Paradigm.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 14 citations in OpenAlex.
- VSIG10L is a major determinant of esophageal homeostasis and inherited predisposition to Barrett's esophagus.Nature communications · 2026Article
- Health risk factors in different educational groups and their association to Barrett's esophagus.Wiener klinische Wochenschrift · 2026Article
- Socioeconomic traits and the risk of Barrett's esophagus and gastroesophageal reflux disease: A Mendelian randomization study.World journal of gastrointestinal oncology · 2024Article
- Association of educational attainment with esophageal cancer, Barrett's esophagus, and gastroesophageal reflux disease, and the mediating role of modifiable risk factors: A Mendelian randomization study.Frontiers in public health · 2023Article
- Development and validation of a risk prediction model to diagnose Barrett's oesophagus (MARK-BE): a case-control machine learning approach.The Lancet. Digital health · 2020Article
- Interactive decision support for esophageal adenocarcinoma screening and surveillance.BMC gastroenterology · 2019Article
- Natural History of Barrett's Esophagus.Digestive diseases and sciences · 2018Review
- Precision care for Barrett's esophagus.Translational gastroenterology and hepatology · 2018Review
- The Evolving Genomic Landscape of Barrett's Esophagus and Esophageal Adenocarcinoma.Gastroenterology · 2017Review
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Authors and funding
20 authors at 1 institution in 1 country.
Funding
Abstract
backgroundBarrett's esophagus is often asymptomatic and only a small portion of Barrett's esophagus patients are currently diagnosed and under surveillance. Therefore, it is important to develop risk prediction models to identify high-risk individuals with Barrett's esophagus. Familial aggregation of Barrett's esophagus and esophageal adenocarcinoma, and the increased risk of esophageal adenocarcinoma for individuals with a family history, raise the necessity of including genetic factors in the prediction model. Methods to determine risk prediction models using both risk covariates and ascertained family data are not well developed.
methodsWe developed a Barrett's Esophagus Translational Research Network (BETRNet) risk prediction model from 787 singly ascertained Barrett's esophagus pedigrees and 92 multiplex Barrett's esophagus pedigrees, fitting a multivariate logistic model that incorporates family history and clinical risk factors. The eight risk factors, age, sex, education level, parental status, smoking, heartburn frequency, regurgitation frequency, and use of acid suppressant, were included in the model. The prediction accuracy was evaluated on the training dataset and an independent validation dataset of 643 multiplex Barrett's esophagus pedigrees.
resultsOur results indicate family information helps to predict Barrett's esophagus risk, and predicting in families improves both prediction calibration and discrimination accuracy.
conclusionsOur model can predict Barrett's esophagus risk for anyone with family members known to have, or not have, had Barrett's esophagus. It can predict risk for unrelated individuals without knowing any relatives' information. IMPACT: Our prediction model will shed light on effectively identifying high-risk individuals for Barrett's esophagus screening and surveillance, consequently allowing intervention at an early stage, and reducing mortality from esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 25(5); 727-35. ©2016 AACR.
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