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Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study

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 gastr...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709770/
https://www.ncbi.nlm.nih.gov/pubmed/30926654
http://dx.doi.org/10.1136/gutjnl-2018-317556
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author 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
author_facet 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
author_sort Cai, Quancai
collection PubMed
description 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-Helicobacter pylori 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, H. pylori 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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spelling pubmed-67097702019-09-09 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 Gut Stomach 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-Helicobacter pylori 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, H. pylori 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. BMJ Publishing Group 2019-09 2019-03-29 /pmc/articles/PMC6709770/ /pubmed/30926654 http://dx.doi.org/10.1136/gutjnl-2018-317556 Text en © Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ. This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
spellingShingle Stomach
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
Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study
title Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study
title_full Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study
title_fullStr Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study
title_full_unstemmed Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study
title_short Development and validation of a prediction rule for estimating gastric cancer risk in the Chinese high-risk population: a nationwide multicentre study
title_sort development and validation of a prediction rule for estimating gastric cancer risk in the chinese high-risk population: a nationwide multicentre study
topic Stomach
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709770/
https://www.ncbi.nlm.nih.gov/pubmed/30926654
http://dx.doi.org/10.1136/gutjnl-2018-317556
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