In China, regional organized esophageal cancer screening programs have been implemented since 2005. However, the implementation of these screening programs is still facing some urgent challenges, especially concerning identifying high-risk individuals. This study aimed to evaluate the risk stratification potential of the current initial assessment strategy used in a mass esophageal squamous cell carcinoma (ESCC) screening program in China.
A total of 43,875 participants without prior cancer history enrolled in a mass ESCC screening program in China from 2007 to 2010 who had initial assessment results were included in this study and were followed until December 31, 2015. Eight potential risk factors for ESCC were evaluated in the initial assessment strategy. A comprehensive evaluation of the association of the initial assessment results with ESCC risk was performed by propensity score matching and Cox regression analysis.
During a median follow-up of 5.5 years, 272 individuals developed ESCC. The high-risk population assessed at baseline had a higher risk of ESCC than the non-high-risk population, with a hazard ratio (HR) of 3.11 (95% confidence interval (CI), 2.33-4.14) after adjustment for sex, age, education level, income level, and body mass index. Additionally, the initial assessment results of the high-risk population were significantly associated with the risk of all esophageal cancers (HR, 3.30; 95% CI, 2.51-4.33) and upper gastrointestinal cancers (HR, 3.03; 95% CI, 2.43-3.76).
The initial screening tool in a mass ESCC screening program in China, consisting of eight accessible variables in epidemiological surveys, could be helpful for the selection of asymptomatic individuals for priority ESCC screening.
Copyright © 2020 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.
About The Expert
Wanqing Chen
He Li
Rongshou Zheng
Jiansong Ren
Jufang Shi
Maomao Cao
Dianqin Sun
Xibin Sun
Xiaoqin Cao
Jinyi Zhou
Pengfei Luo
Jialin Wang
Hengmin Ma
Tiantang Shao
Chunling Zhao
Shilin He
Daokuan Sun
Yuluan Xu
Pengli Wu
Hongmei Zeng
Jiang Li
Jie He
References
PubMed