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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...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2019
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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. |
format | Online Article Text |
id | pubmed-6709770 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BMJ Publishing Group |
record_format | MEDLINE/PubMed |
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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