ArticleCancer prevention research (Philadelphia, Pa.)2012
A clinical risk prediction model for Barrett esophagus.
Article in Cancer prevention research (Philadelphia, Pa.), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 4 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
38 citing papers in PubMed, 4 syntheses or guidelines pooled it, 79 citations in OpenAlex.
- Systematic mapping of registered interventional studies addressing the top 10 research priorities in Barrett's oesophagus and gastro-oesophageal reflux disease.BMJ open gastroenterology · 2025Pooled it
- Lifestyle interventions can reduce the risk of Barrett's esophagus: a systematic review and meta-analysis of 62 studies involving 250,157 participants.Cancer medicine · 2021Pooled it
- ACG Clinical Guideline: Diagnosis and Management of Barrett's Esophagus.The American journal of gastroenterology · 2016Guideline
- Alcohol consumption and the risk of Barrett's esophagus: a comprehensive meta-analysis.Scientific reports · 2015Pooled it
- Screening for Barrett's esophagus and esophageal adenocarcinoma: recent advances and next steps.Diseases of the esophagus : official journal of the International Society for Diseases of the Esophagus · 2026Review
- Endoscopic Screening of Barrett's Esophagus.Gastrointestinal endoscopy clinics of North America · 2026Review
- Development and validation of a risk prediction model for gastroesophageal reflux disease: Gastroesophageal Reflux Disease Risk Scoring System.World journal of gastrointestinal pathophysiology · 2025Article
- New Approaches to Screening for Barrett Esophagus.Gastroenterology & hepatology · 2025Article
- Cost-effective identification of Barrett's esophagus in the community: A first step towards screening.Journal of gastroenterology and hepatology · 2024Article
- Development of a prediction score for Barrett's esophagus in Japanese health checkup settings.Esophagus : official journal of the Japan Esophageal Society · 2024Article
- Advances in Screening for Barrett Esophagus and Esophageal Adenocarcinoma.Mayo Clinic proceedings · 2024Review
- Predicting Incident Adenocarcinoma of the Esophagus or Gastric Cardia Using Machine Learning of Electronic Health Records.Gastroenterology · 2023Article
- A personalized and dynamic risk estimation model: The new paradigm in Barrett's esophagus surveillance.PloS one · 2022Article
- Global burden and epidemiology of Barrett oesophagus and oesophageal cancer.Nature reviews. Gastroenterology & hepatology · 2021Review
- Risk Prediction of Barrett's Esophagus in a Taiwanese Health Examination Center Based on Regression Models.International journal of environmental research and public health · 2021Article
- Risk Prediction Models for Barrett's Esophagus Discriminate Well and Are Generalizable in an External Validation Study.Digestive diseases and sciences · 2020Article
- Validation and Comparison of Tools for Selecting Individuals to Screen for Barrett's Esophagus and Early Neoplasia.Gastroenterology · 2020Article
- 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
- Barrett's Esophagus and Esophageal Adenocarcinoma: How Common Are They Really?Digestive diseases and sciences · 2018Review
- Epigenome-based cancer risk prediction: rationale, opportunities and challenges.Nature reviews. Clinical oncology · 2018Review
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
Barrett esophagus is the only known precursor to esophageal adenocarcinoma. As definitive diagnosis requires costly endoscopic investigation, we sought to develop a risk prediction model to aid in deciding which patients with gastroesophageal reflux symptoms to refer for endoscopic screening for Barrett esophagus. The study included data from patients with incident nondysplastic Barrett esophagus (n = 285) and endoscopy control patients with esophageal inflammatory changes without Barrett esophagus ("inflammation controls", n = 313). We used two phases of stepwise backwards logistic regression to identify the important predictors for Barrett esophagus in men and women separately: first, including all significant covariates from univariate analyses and then fitting non-significant covariates from univariate analyses to identify those effects detectable only after adjusting for other factors. The final model pooled these predictors and was externally validated for discrimination and calibration using data from a Barrett esophagus study conducted in western Washington State. The final risk model included terms for age, sex, smoking status, body mass index, highest level of education, and frequency of use of acid suppressant medications (area under the ROC curve, 0.70; 95%CI, 0.66-0.74). The model had moderate discrimination in the external dataset (area under the ROC curve, 0.61; 95%CI, 0.56-0.66). The model was well calibrated (Hosmer-Lemeshow test, P = 0.75), with predicted probability and observed risk highly correlated. The prediction model performed reasonably well and has the potential to be an effective and useful clinical tool in selecting patients with gastroesophageal reflux symptoms to refer for endoscopic screening for Barrett esophagus.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.