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共1篇 平均IF=25.8 (25.8-25.8)更多分析
  • 1区Q1影响因子: 25.8
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    1. Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study.
    1. 估算中国高风险群体胃癌风险预测规则的发展与验证:全国多期几项研究。
    作者: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 ,
    期刊:Gut
    日期:2019-03-29
    DOI :10.1136/gutjnl-2018-317556
    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.
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