Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model
This study aimed at evaluating the efficacy of the questionnaire-based prediction model in an independent prospective cohort. A cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015-2017. A total of 182 villages/communities were regarded...
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Veröffentlicht in: | Chinese journal of cancer research 2020-10, Vol.32 (5), p.605-613 |
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creator | Cao, Maomao Li, He Sun, Dianqin Lei, Lin Ren, Jiansong Shi, Jufang Li, Ni Peng, Ji Chen, Wanqing |
description | This study aimed at evaluating the efficacy of the questionnaire-based prediction model in an independent prospective cohort.
A cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015-2017. A total of 182 villages/communities were regarded as clusters, and allocated to screening arm or control arm randomly. Face-to-face interview through a questionnaire interview, including of relevant risk factors of gastric cancer, was administered for each subject. Participants were further classified into high-risk or low-risk groups based on their exposure to risk factors. All participants were followed up until December 31, 2019. Cumulative incidence rates from gastric cancer between high-risk and low-risk groups were calculated and compared using the log-rank test. Cox proportional hazard regression models were applied to estimate hazard ratio (HR) and 95% confidence interval (95% CI).
Totally, 89,914 residents were recruited with a mean follow-up of 3.47 years. And 42,015 (46.73%) individuals were classified into high-risk group and 47,899 (53.27%) subjects were categorized into low-risk group. Gastric cancer was diagnosed in 131 participants, of which 91 were in high-risk group. Compared with the low-risk participants, high-risk individuals were more likely to develop gastric cancer (adjusted HR=2.15, 95% CI, 1.23-3.76). The sensitivity of the questionnaire-based model was estimated at 61.82% (95% CI, 47.71-74.28) in a general population.
Our questionnaire-based model is effective at identifying high-risk individuals for gastric cancer. |
doi_str_mv | 10.21147/j.issn.1000-9604.2020.05.05 |
format | Article |
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A cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015-2017. A total of 182 villages/communities were regarded as clusters, and allocated to screening arm or control arm randomly. Face-to-face interview through a questionnaire interview, including of relevant risk factors of gastric cancer, was administered for each subject. Participants were further classified into high-risk or low-risk groups based on their exposure to risk factors. All participants were followed up until December 31, 2019. Cumulative incidence rates from gastric cancer between high-risk and low-risk groups were calculated and compared using the log-rank test. Cox proportional hazard regression models were applied to estimate hazard ratio (HR) and 95% confidence interval (95% CI).
Totally, 89,914 residents were recruited with a mean follow-up of 3.47 years. And 42,015 (46.73%) individuals were classified into high-risk group and 47,899 (53.27%) subjects were categorized into low-risk group. Gastric cancer was diagnosed in 131 participants, of which 91 were in high-risk group. Compared with the low-risk participants, high-risk individuals were more likely to develop gastric cancer (adjusted HR=2.15, 95% CI, 1.23-3.76). The sensitivity of the questionnaire-based model was estimated at 61.82% (95% CI, 47.71-74.28) in a general population.
Our questionnaire-based model is effective at identifying high-risk individuals for gastric cancer.</description><identifier>ISSN: 1000-9604</identifier><identifier>EISSN: 1993-0631</identifier><identifier>DOI: 10.21147/j.issn.1000-9604.2020.05.05</identifier><identifier>PMID: 33223755</identifier><language>eng</language><publisher>China: Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China%Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China</publisher><subject>Original</subject><ispartof>Chinese journal of cancer research, 2020-10, Vol.32 (5), p.605-613</ispartof><rights>Copyright © 2020 Chinese Journal of Cancer Research. All rights reserved.</rights><rights>Copyright © Wanfang Data Co. Ltd. All Rights Reserved.</rights><rights>Copyright © 2020 Chinese Journal of Cancer Research. All rights reserved. 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c394t-b29641993b6b1d07e7b7b371d2cd961d45514e565bce68658b796b31d78dba953</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttp://www.wanfangdata.com.cn/images/PeriodicalImages/zgazyj/zgazyj.jpg</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666781/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7666781/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33223755$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Cao, Maomao</creatorcontrib><creatorcontrib>Li, He</creatorcontrib><creatorcontrib>Sun, Dianqin</creatorcontrib><creatorcontrib>Lei, Lin</creatorcontrib><creatorcontrib>Ren, Jiansong</creatorcontrib><creatorcontrib>Shi, Jufang</creatorcontrib><creatorcontrib>Li, Ni</creatorcontrib><creatorcontrib>Peng, Ji</creatorcontrib><creatorcontrib>Chen, Wanqing</creatorcontrib><creatorcontrib>Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China</creatorcontrib><creatorcontrib>Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China</creatorcontrib><title>Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model</title><title>Chinese journal of cancer research</title><addtitle>Chin J Cancer Res</addtitle><description>This study aimed at evaluating the efficacy of the questionnaire-based prediction model in an independent prospective cohort.
A cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015-2017. A total of 182 villages/communities were regarded as clusters, and allocated to screening arm or control arm randomly. Face-to-face interview through a questionnaire interview, including of relevant risk factors of gastric cancer, was administered for each subject. Participants were further classified into high-risk or low-risk groups based on their exposure to risk factors. All participants were followed up until December 31, 2019. Cumulative incidence rates from gastric cancer between high-risk and low-risk groups were calculated and compared using the log-rank test. Cox proportional hazard regression models were applied to estimate hazard ratio (HR) and 95% confidence interval (95% CI).
Totally, 89,914 residents were recruited with a mean follow-up of 3.47 years. And 42,015 (46.73%) individuals were classified into high-risk group and 47,899 (53.27%) subjects were categorized into low-risk group. Gastric cancer was diagnosed in 131 participants, of which 91 were in high-risk group. Compared with the low-risk participants, high-risk individuals were more likely to develop gastric cancer (adjusted HR=2.15, 95% CI, 1.23-3.76). The sensitivity of the questionnaire-based model was estimated at 61.82% (95% CI, 47.71-74.28) in a general population.
Our questionnaire-based model is effective at identifying high-risk individuals for gastric cancer.</description><subject>Original</subject><issn>1000-9604</issn><issn>1993-0631</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><recordid>eNpVUV2LFDEQDKJ4H_oXZB4EfZmxk0ySHZEDWe5UOPBF34SQrxkzZpM12VnZ-_XO7N4dCg1p6EpVdRdCrzE0BONWvBsbX0psMADUHYe2IUCgATbXE3SOu47WwCl-OvcPkDN0UcoIwAQD_BydUUoIFYydox_roErx_cHHocq-_KqC27tQpb4aVNllbyqjonH5fXW9V2FSO5_iMv09ubL0Ufnsaq2Ks9U2O-vNEbFJ1oUX6FmvQnEv799L9P3m-tv6c3379dOX9cfb2tCu3dWadLxdfGuusQXhhBaaCmyJsR3HtmUMt45xpo3jK85WWnRcU2zFymrVMXqJrk6820lvnDUu7rIKcpv9RuWDTMrL_yfR_5RD2kvBORcrPBO8ORH8UbFXcZBjmnKcLcu7Qd0dxuXCwOaakW_vpXI6nkBufDEuBBVdmookLaccMKdkhn44QU1OpWTXPxrCII9RylEuUcolJ7nkJBchCUwelV79u9Tj54fs6F9gd53u</recordid><startdate>20201031</startdate><enddate>20201031</enddate><creator>Cao, Maomao</creator><creator>Li, He</creator><creator>Sun, Dianqin</creator><creator>Lei, Lin</creator><creator>Ren, Jiansong</creator><creator>Shi, Jufang</creator><creator>Li, Ni</creator><creator>Peng, Ji</creator><creator>Chen, Wanqing</creator><general>Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China%Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China</general><general>AME Publishing Company</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope><scope>5PM</scope></search><sort><creationdate>20201031</creationdate><title>Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model</title><author>Cao, Maomao ; Li, He ; Sun, Dianqin ; Lei, Lin ; Ren, Jiansong ; Shi, Jufang ; Li, Ni ; Peng, Ji ; Chen, Wanqing</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c394t-b29641993b6b1d07e7b7b371d2cd961d45514e565bce68658b796b31d78dba953</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Original</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Maomao</creatorcontrib><creatorcontrib>Li, He</creatorcontrib><creatorcontrib>Sun, Dianqin</creatorcontrib><creatorcontrib>Lei, Lin</creatorcontrib><creatorcontrib>Ren, Jiansong</creatorcontrib><creatorcontrib>Shi, Jufang</creatorcontrib><creatorcontrib>Li, Ni</creatorcontrib><creatorcontrib>Peng, Ji</creatorcontrib><creatorcontrib>Chen, Wanqing</creatorcontrib><creatorcontrib>Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China</creatorcontrib><creatorcontrib>Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Chinese journal of cancer research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Maomao</au><au>Li, He</au><au>Sun, Dianqin</au><au>Lei, Lin</au><au>Ren, Jiansong</au><au>Shi, Jufang</au><au>Li, Ni</au><au>Peng, Ji</au><au>Chen, Wanqing</au><aucorp>Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China</aucorp><aucorp>Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model</atitle><jtitle>Chinese journal of cancer research</jtitle><addtitle>Chin J Cancer Res</addtitle><date>2020-10-31</date><risdate>2020</risdate><volume>32</volume><issue>5</issue><spage>605</spage><epage>613</epage><pages>605-613</pages><issn>1000-9604</issn><eissn>1993-0631</eissn><abstract>This study aimed at evaluating the efficacy of the questionnaire-based prediction model in an independent prospective cohort.
A cluster-randomized controlled trial was conducted in Changsha, Harbin, Luoshan, and Sheyang in eastern China in 2015-2017. A total of 182 villages/communities were regarded as clusters, and allocated to screening arm or control arm randomly. Face-to-face interview through a questionnaire interview, including of relevant risk factors of gastric cancer, was administered for each subject. Participants were further classified into high-risk or low-risk groups based on their exposure to risk factors. All participants were followed up until December 31, 2019. Cumulative incidence rates from gastric cancer between high-risk and low-risk groups were calculated and compared using the log-rank test. Cox proportional hazard regression models were applied to estimate hazard ratio (HR) and 95% confidence interval (95% CI).
Totally, 89,914 residents were recruited with a mean follow-up of 3.47 years. And 42,015 (46.73%) individuals were classified into high-risk group and 47,899 (53.27%) subjects were categorized into low-risk group. Gastric cancer was diagnosed in 131 participants, of which 91 were in high-risk group. Compared with the low-risk participants, high-risk individuals were more likely to develop gastric cancer (adjusted HR=2.15, 95% CI, 1.23-3.76). The sensitivity of the questionnaire-based model was estimated at 61.82% (95% CI, 47.71-74.28) in a general population.
Our questionnaire-based model is effective at identifying high-risk individuals for gastric cancer.</abstract><cop>China</cop><pub>Office for Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China%Department of Cancer Prevention and Control, Shenzhen Center for Chronic Disease Control, Shenzhen 518020, China</pub><pmid>33223755</pmid><doi>10.21147/j.issn.1000-9604.2020.05.05</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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title | Classifying risk level of gastric cancer: Evaluation of questionnaire-based prediction model |
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