, Cancer Epidemiology Biomarkers Prevention, 2024 Jan 12
Investigators
Edward Huang, M.D., MPH, Su-Ying Liang, Ph.D., Research Economist / Faculty
Abstract
Gastric adenocarcinoma (GAC) is often diagnosed at advanced stages and portends a poor prognosis. We hypothesized that electronic health records (EHR) could be leveraged to identify individuals at highest risk for GAC from the population seeking routine care.Methods:
This was a retrospective cohort study, with endpoint of GAC incidence as ascertained through linkage to an institutional tumor registry. We utilized 2010–2020 data from the Palo Alto Medical Foundation, a large multispecialty practice serving Northern California. The analytic cohort comprised individuals ages 40–75 receiving regular ambulatory care. Variables collected included demographic, medical, pharmaceutical, social, and familial data. Electronic phenotyping was based on rule-based methods.
Results:The cohort comprised 316,044 individuals and approximately 2 million person-years (p-y) of observation. 157 incident GACs occurred (incidence 7.9 per 100,000 p-y), of which 102 were non-cardia GACs (incidence 5.1 per 100,000 p-y). In multivariable analysis, male sex [HR: 2.2, 95% confidence interval (CI): 1.6–3.1], older age, Asian race (HR: 2.5, 95% CI: 1.7–3.7), Hispanic ethnicity (HR: 1.9, 95% CI: 1.1–3.3), atrophic gastritis (HR: 4.6, 95% CI: 2.2–9.3), and anemia (HR: 1.9, 95% CI: 1.3–2.6) were associated with GAC risk; use of NSAID was inversely associated (HR: 0.3, 95% CI: 0.2–0.5). Older age, Asian race, Hispanic ethnicity, atrophic gastritis, and anemia were associated with non-cardia GAC.
Conclusions:Routine EHR data can stratify the general population for GAC risk.
Impact:Such methods may help triage populations for targeted screening efforts, such as upper endoscopy.