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Tian et al. aimed to develop and optimize a comprehensive risk model covering all stages of the dynamic adenoma-carcinoma sequence. They built and validated three trans-ancestry polygenic risk score strategies, assessed across independent screening datasets, and tested the optimal score combined with lifestyle factors in large prospective cohorts.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/developing-an-optimal-stratification-model-for-colorectal-cancer-screening-and-reducing-racial-disparities-in-multi-center-population-based-studies/332139/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/developing-an-optimal-stratification-model-for-colorectal-cancer-screening-and-reducing-racial-disparities-in-multi-center-population-based-studies/332139.png","ImageObject",300,407,{"name":92,"@type":93},"Hazel","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-04","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What problem does the study address for colorectal cancer screening?","Question",{"text":112,"@type":113},"The study targets the lack of effective risk prediction models for personalized CRC early screening in East Asian populations, aiming to improve early detection across the adenoma-carcinoma sequence.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were the risk prediction models developed and compared?",{"text":117,"@type":113},"Three trans-ancestry polygenic risk score approaches were constructed, including locus-based and genome-wide Bayesian methods, and each was evaluated and validated in independent screening datasets.",{"name":119,"@type":110,"acceptedAnswer":120},"What was the key finding about the best-performing risk score?",{"text":121,"@type":113},"Among the tested models, PRS 183 showed the optimal discriminatory ability in both East Asian and European validation datasets, and combining PRS 183 with lifestyle factors improved overall risk stratification performance.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},332139,1790218701,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},137441390410,"https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984","Tian et al. Genome Medicine (2024) 16:81 [https://doi.org/10.1186/s13073-024-01355-y](https://doi.org/10.1186/s13073-024-01355-y)  \nGenome Medicine  \n RESEARCH Open Access  \nDeveloping an optimal stratification  \nmodel for colorectal cancer screening and reducing racial disparities in multi-center population-based studies  \nJianboTian1,2*†, Ming Zhang1,2†, Fuwei Zhang1,2†, Kai Gao3,4†, Zequn Lu5, Yimin Cai5, Can Chen5, Caibo Ning5, Yanmin Li5, Sangni Qian3,4, Hao Bai3,4, Yizhuo Liu5, Heng Zhang5, Shuoni Chen5, Xiangpan Li2, Yongchang Wei6, Bin Li5, Ying Zhu5, Jinhua Yang7, Mingjuan Jin3,4*, Xiaoping Miao 1,2,8* and Kun Chen3,4*  \nAbstract  \nBackground Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages ofthe dynamic adenoma-carcinoma sequence in EAS population.  \nMethods To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from largescale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with nonadvanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants.  \nResults Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS 183 demonstrated the optimal discriminatory ability  \n†JianboTian, Ming Zhang, Fuwei Zhang and Kai Gao contributed equally to this work.  \n*Correspondence: JianboTian [tianjb@whu.edu.cn](tianjb@whu.edu.cn)[ ](tianjb@whu.edu.cn)Mingjuan Jin [jinmj@zju.edu.cn](jinmj@zju.edu.cn)[ ](jinmj@zju.edu.cn)Xiaoping Miao [xpmiao@whu.edu.cn](xpmiao@whu.edu.cn)[ ](xpmiao@whu.edu.cn)Kun Chen [ck@zju.edu.cn](ck@zju.edu.cn)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ()[. The Creative Commons Public Domain Dedication waiver (](http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ()[http://creativecom](http://creativecom)[mons.","cbCaidaR0MijSmfe","https://ap.wps.com/l/cbCaidaR0MijSmfe","pdf",7346876,22,"English","# Abstract\n## Background\n## Methods\n## Results\n## Conclusions\n# Graphical Abstract\n## Background","[{\"question\":\"What problem does the study address for colorectal cancer screening?\",\"answer\":\"The study targets the lack of effective risk prediction models for personalized CRC early screening in East Asian populations, aiming to improve early detection across the adenoma-carcinoma sequence.\"},{\"question\":\"How were the risk prediction models developed and compared?\",\"answer\":\"Three trans-ancestry polygenic risk score approaches were constructed, including locus-based and genome-wide Bayesian methods, and each was evaluated and validated in independent screening datasets.\"},{\"question\":\"What was the key finding about the best-performing risk score?\",\"answer\":\"Among the tested models, PRS 183 showed the optimal discriminatory ability in both East Asian and European validation datasets, and combining PRS 183 with lifestyle factors improved overall risk stratification performance.\"}]","Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies | PDF",1789996990,55]