ArticleDigestive diseases and sciences2022
Risk Score Using Demographic and Clinical Risk Factors Predicts Gastric Intestinal Metaplasia Risk in a U.S. Population.
Article in Digestive diseases and sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 9 citations in OpenAlex.
- Metabolic Factors Associated with Endoscopic Atrophy, Intestinal Metaplasia, and Gastric Neoplasms inClinics and practice · 2024Article
- Using the Electronic Health Record to Develop a Gastric Cancer Risk Prediction Model.Gastro hep advances · 2024Article
- Stomach Cancer Prediction Model (SCoPM): An approach to risk stratification in a diverse U.S. population.PloS one · 2024Article
- Validation of a pre-endoscopy risk score for predicting the presence of gastric intestinal metaplasia in a U.S. population.Gastrointestinal endoscopy · 2023Article
- Evaluation of polygenic risk score for risk prediction of gastric cancer.World journal of gastrointestinal oncology · 2023Review
- Impact of Comorbid Psychiatric Disorders on Healthcare Utilization in Patients with Inflammatory Bowel Disease: A Nationally Representative Cohort Study.Digestive diseases and sciences · 2022Article
- Prevalence of Hospitalization and Readmission in Patients with Inflammatory Bowel Diseases.Digestive diseases and sciences · 2022Article
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Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
BACKGROUND/
aimsScreening for gastric intestinal metaplasia (GIM) may lead to early gastric cancer detection. We developed and validated a pre-endoscopy risk prediction model for detection of GIM based on patient-level risk factors in a U.S. POPULATION:
methodsWe used data from 423 GIM cases and 1796 controls from a cross-sectional study among primary care and endoscopy clinic patients at the Houston VA. We developed the model using backwards stepwise regression and assessed discrimination using area under the receiver operating characteristic (AUROC). The model was internally validated using cross-validation and bootstrapping. The final expanded model was compared to a model including H. pylori infection alone and a baseline model including remaining terms without H. pylori.
resultsMale sex, older age, non-white race/ethnicity, smoking status, and H. pylori were associated with GIM risk. The expanded model including these terms had AUROC 0.73 (95%CI 0.71-0.76) for predicting GIM and AUROC 0.82 (95%CI 0.79-0.86) for extensive GIM. This model discriminated better than a model including only H. pylori (AUROC 0.66; 95%CI 0.63-0.68) and the baseline model (AUROC 0.67; 95%CI 0.64-0.70). The expanded model performed similarly among primary care (AUROC 0.75) and endoscopy (AUROC 0.73) patients. The expanded model showed sufficient internal validity (cross-validation AUROC 0.72) with little evidence of over-fitting.
conclusionsWe develop and validate a non-invasive risk model for GIM detection in a U.S. population that included terms for sex, age, race/ethnicity, smoking status, and H. pylori infection. Validated risk models would identify individuals with GIM who should be referred for endoscopic screening.
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