Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study.
Cai Quancai,Zhu Chunping,Yuan Yuan,Feng Qi,Feng Yichao,Hao Yingxia,Li Jichang,Zhang Kaiguang,Ye Guoliang,Ye Liping,Lv Nonghua,Zhang Shengsheng,Liu Chengxia,Li Mingquan,Liu Qi,Li Rongzhou,Pan Jie,Yang Xiaocui,Zhu Xuqing,Li Yumei,Lao Bo,Ling Ansheng,Chen Honghui,Li Xiuling,Xu Ping,Zhou Jianfeng,Liu Baozhen,Du Zhiqiang,Du Yiqi,Li Zhaoshen,
OBJECTIVE:To develop a gastric cancer (GC) risk prediction rule as an initial prescreening tool to identify individuals with a high risk prior to gastroscopy. DESIGN:This was a nationwide multicentre cross-sectional study. Individuals aged 40-80 years who went to hospitals for a GC screening gastroscopy were recruited. Serum pepsinogen (PG) I, PG II, gastrin-17 (G-17) and anti- IgG antibody concentrations were tested prior to endoscopy. Eligible participants (n=14 929) were randomly assigned into the derivation and validation cohorts, with a ratio of 2:1. Risk factors for GC were identified by univariate and multivariate analyses and an optimal prediction rule was then settled. RESULTS:The novel GC risk prediction rule comprised seven variables (age, sex, PG I/II ratio, G-17 level, infection, pickled food and fried food), with scores ranging from 0 to 25. The observed prevalence rates of GC in the derivation cohort at low-risk (≤11), medium-risk (12-16) or high-risk (17-25) group were 1.2%, 4.4% and 12.3%, respectively (p<0.001).When gastroscopy was used for individuals with medium risk and high risk, 70.8% of total GC cases and 70.3% of early GC cases were detected. While endoscopy requirements could be reduced by 66.7% according to the low-risk proportion. The prediction rule owns a good discrimination, with an area under curve of 0.76, or calibration (p<0.001). CONCLUSIONS:The developed and validated prediction rule showed good performance on identifying individuals at a higher risk in a Chinese high-risk population. Future studies are needed to validate its efficacy in a larger population.