Related Experiment Video
Updated: Jul 1, 2026

Establishment and Evaluation of a Risk Prediction Model for Pathological Escalation of Gastric Low-Grade Intraepithelial Neoplasia
Published on: February 16, 2024
Risk score for esophageal and gastric cancer in the over 50-year-old population based on self-reported information
Timo Schmitz1, Julia Reizner2, Sha Sha3
1Epidemiology, Medical Faculty, University of Augsburg, Augsburg, Germany. timo.schmitz@med.uni-augsburg.de.
Background:
The aim was to build a risk score (RS) for gastric and esophageal cancer (GEC) based on self-reported information as a first step to develop a risk-adapted screening modality for GEC or precursor lesions in a non-high incidence region in the framework of the RISC-GAP project.
Methods:
Data from 375,280 participants aged 50 years and older in the UK Biobank project were used. The outcome was incident esophageal or gastric cancer. Various variables, including sociodemographic data, medical conditions, medication, lifestyle factors and diet, were initially considered. To be able to use the RS as a screening tool in the general population, only variables that can be determined by self-report were selected. For variable selection, we used COX regression models with LASSO penalization; the main criterion was 5- and 10-years AUC.
Results:
The final score included the following eight variables: sex, age, smoking status, drinking status, body mass index, history of esophagitis, medication with gastric acid inhibitors and surgery in the stomach/esophagus area. 10-fold cross-validation revealed a discrimination of 0.740 (5-year AUC) and 0.724 (10-year AUC), respectively. High-risk individuals were defined as those with a 10-year cancer risk of 1% or more (around 6% of the study population).
Conclusion:
The RS allows a reasonable discrimination of individuals with an elevated risk of gastric or esophageal cancer. In further steps of the RISC-GAP project it will be evaluated whether selection of a high-risk population can be further improved by additional clinical and biomarker information.
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