Publication Date

9-1-2022

Journal

Digestive Diseases and Sciences

DOI

10.1007/s10620-021-07309-3

PMID

34797447

PMCID

PMC9117573

PubMedCentral® Posted Date

9-1-2023

PubMedCentral® Full Text Version

Author MSS

Published Open-Access

yes

Keywords

Cross-Sectional Studies, Demography, Endoscopy, Gastrointestinal, Helicobacter Infections, Helicobacter pylori, Humans, Male, Metaplasia, Precancerous Conditions, Risk Factors, Stomach Neoplasms, gastric intestinal metaplasia, gastric cancer, risk prediction, epidemiology, Helicobacter pylori

Abstract

BACKGROUND/AIMS: Screening 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.

METHODS: We 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.

RESULTS: Male 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.

CONCLUSIONS: We 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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