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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


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          To develop a gastric cancer (GC) risk prediction rule as an initial prescreening tool to identify individuals with a high risk prior to gastroscopy.


          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.


          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).


          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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          Most cited references40

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          Classification and grading of gastritis. The updated Sydney System. International Workshop on the Histopathology of Gastritis, Houston 1994.

          The Sydney System for the classification of gastritis emphasized the importance of combining topographical, morphological, and etiological information into a schema that would help to generate reproducible and clinically useful diagnoses. To reappraise the Sydney System 4 years after its introduction, a group of gastrointestinal pathologists from various parts of the world met in Houston, Texas, in September 1994. The aims of the workshop were (a) to establish an agreed terminology of gastritis; (b) to identify, define, and attempt to resolve some of the problems associated with the Sydney System. This article introduces the Sydney System as it was revised at the Houston Gastritis Workshop and represents the consensus of the participants. Overall, the principles and grading of the Sydney System were only slightly modified, the grading being aided by the provision of a visual analogue scale. The terminology of the final classification has been improved to emphasize the distinction between the atrophic and nonatrophic stomach; the names used for each entity were selected because they are generally acceptable to both pathologists and gastroenterologists. In addition to the main categories and atrophic and nonatrophic gastritis, the special or distinctive forms are described and their respective diagnostic criteria are provided. The article includes practical guidelines for optimal biopsy sampling of the stomach, for the use of the visual analogue scales for grading the histopathologic features, and for the formulation of a comprehensive standardized diagnosis. A glossary of gastritis-related terms as used in this article is provided.
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            Internal validation of predictive models: efficiency of some procedures for logistic regression analysis.

            The performance of a predictive model is overestimated when simply determined on the sample of subjects that was used to construct the model. Several internal validation methods are available that aim to provide a more accurate estimate of model performance in new subjects. We evaluated several variants of split-sample, cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for 30-day mortality after an acute myocardial infarction. Random samples with a size between n = 572 and n = 9165 were drawn from a large data set (GUSTO-I; n = 40,830; 2851 deaths) to reflect modeling in data sets with between 5 and 80 events per variable. Independent performance was determined on the remaining subjects. Performance measures included discriminative ability, calibration and overall accuracy. We found that split-sample analyses gave overly pessimistic estimates of performance, with large variability. Cross-validation on 10% of the sample had low bias and low variability, but was not suitable for all performance measures. Internal validity could best be estimated with bootstrapping, which provided stable estimates with low bias. We conclude that split-sample validation is inefficient, and recommend bootstrapping for estimation of internal validity of a predictive logistic regression model.
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                Author and article information

                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                September 2019
                29 March 2019
                : 68
                : 9
                : 1576-1587
                [1 ] departmentDepartment of Gastroenterology , Changhai Hospital, Naval Medical University , Shanghai, China
                [2 ] departmentTumor Etiology and Screening Department , China Medical University , Shenyang, China
                [3 ] departmentDepartment of Gastroenterology , Mianyang Central Hospital , Mianyang, China
                [4 ] departmentDepartment of Gastroenterology , Affiliated Hospital of Yan’an University , Yanan, China
                [5 ] departmentDepartment of Gastroenterology , Baoding First Central Hospital , Baoding, China
                [6 ] departmentDepartment of Gastroenterology , Baoji Central Hospital , Baoji, China
                [7 ] departmentDepartment of Gastroenterology , Anhui Provincial Hospital , Hefei, China
                [8 ] departmentDepartment of Gastroenterology , Affiliated Hospital of Ningbo University , Ningbo, China
                [9 ] departmentDepartment of Gastroenterology , Taizhou Hospital , Taizhou, China
                [10 ] departmentDepartment of Gastroenterology , First Affiliated Hospital of Nanchang University , NanChang, China
                [11 ] departmentDepartment of Gastroenterology , Beijing Traditional Chinese Medicine Hospital of Capital Medical University , Beijing, China
                [12 ] departmentDepartment of Gastroenterology , Affiliated Hospital of Binzhou Medical College , Binzhou, China
                [13 ] departmentDepartment of Gastroenterology , Yan’an People’s Hospital , Yan’an, China
                [14 ] departmentDepartment of Gastroenterology , Affiliated Hospital of Guizhou Medical University , Guiyang, China
                [15 ] departmentDepartment of Gastroenterology , Ruian People’s Hospital , Rui’an, China
                [16 ] departmentDepartment of Gastroenterology , Wenzhou Central Hospital , Wenzhou, China
                [17 ] departmentDepartment of Gastroenterology , Ankang Central Hospital , Ankang, China
                [18 ] departmentDepartment of Gastroenterology , Taizhou Municipal Hospital , Taizhou, China
                [19 ] departmentDepartment of Gastroenterology , Zhejiang General Team Hospital of Chinese People’s Armed Police Force , Hangzhou, China
                [20 ] departmentDepartment of Gastroenterology , Ningbo Yinzhou District Second Hospital , Ningbo, China
                [21 ] departmentDepartment of Gastroenterology , Anqing First People’s Hospital , Anqing, China
                [22 ] departmentDepartment of Gastroenterology , Second Affiliated Hospital of South China University , Hengyang, China
                [23 ] departmentDepartment of Gastroenterology , Henan Provincial People’s Hospital , Zhengzhou, China
                [24 ] departmentDepartment of Gastroenterology , Shanghai Songjiang Distict Central Hospital , Shanghai, China
                [25 ] departmentDepartment of Gastroenterology , Ningbo Beilun District Xiaogang Hospital , Ningbo, China
                [26 ] departmentDepartment of Gastroenterology , Binzhou People’s Hospital , Binzhou, China
                [27 ] departmentDepartment of Gastroenterology , Jianyang People’s Hospital , Jianyang, China
                Author notes
                [Correspondence to ] Prof Yiqi Du and Prof Zhaoshen Li, Department of Gastroenterology, Changhai Hospital, Naval Medical University, Shanghai 200433, China; duyiqi@ 123456hotmail.com , zhsl@ 123456vip.163.com
                Author information
                © 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/.

                : 09 September 2018
                : 08 March 2019
                : 12 March 2019
                Funded by: the Ministry of Science and Technology of China;
                Original article
                Custom metadata

                Gastroenterology & Hepatology
                gastric cancer,prescreening,risk stratification,pepsinogen,gastrin-17,helicobacter pylori


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