ArticleGastroenterology report2026
A model for projecting individuals' risk of esophageal squamous cell carcinoma in a high-risk Chinese population.
Article in Gastroenterology report, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Early detection of esophageal squamous cell carcinoma (ESCC) may improve survival, but universal screening is not feasible. This study aimed to develop and validate a model for identifying individuals at high absolute risk of ESCC in a high-risk Chinese population. Methods: The model was developed by using data from a case-control study in Yanting County, Sichuan, China between 2011 and 2013, including 942 ESCC cases and 942 age- and sex-matched control participants. Conditional logistic regression and the Gail algorithm were used to construct the model. Model performance was assessed by using the area under the receiver-operating characteristic curve (AUC) with 10-fold cross-validation. External validation was performed in two independent populations, i.e. another Chinese case-control study and the UK Biobank cohort. Results: The model included six risk factors: education level, marital status, tobacco smoking, alcohol consumption, body mass index (overweight status), and family history of cancer. The model incorporated age- and sex-specific incidence rates in the population to estimate the 5-year absolute risk. The AUC was 0.72 (95% confidence interval [CI] 0.69-0.74) in the derivation dataset and 0.68 (95% CI, 0.67-0.69) after cross-validation. In external validation, the AUC was 0.65 (95% CI, 0.61-0.69) in the independent Chinese case-control study and 0.66 (95% CI, 0.56-0.75) in UK Biobank. The estimated 5-year absolute risk of ESCC in the population in Yanting ranged from 0.0005% to 18.2%. In the group at the highest predicted risk, six individuals would need to undergo screening to detect one ESCC case within 5 years. Conclusion: The developed model demonstrated acceptable performance and has the potential to identify high-risk individuals for targeted prevention and early detection in the studied high-risk population.
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