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Univariate and multivariate Cox regression identified key biomarkers for constructing the score. Results stratified patients into high- and low-risk groups with an AUC of 0.660, and multivariate analysis confirmed G-Risk as an independent prognostic factor. The tool supports more precise, personalized treatment planning.",{"@graph":69,"@context":123},[70,84,106],{"@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":35,"@type":76,"position":81},"https://docshare.wps.com/document/healthcare/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/development-of-the-g-risk-scoring-system-utilizing-inflammatory-and-tumor-biomarkers-to-improve-prognostic-accuracy-in-gastric-cancer-patients-without-lymphovascular-invasion/369406/",{"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/development-of-the-g-risk-scoring-system-utilizing-inflammatory-and-tumor-biomarkers-to-improve-prognostic-accuracy-in-gastric-cancer-patients-without-lymphovascular-invasion/369406.png","ImageObject",300,407,{"name":92,"@type":93},"\tJames","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",11,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What is the main objective of the study?","Question",{"text":113,"@type":114},"The study aims to establish the G-Risk scoring system to enhance prognostic accuracy for gastric cancer patients without lymphovascular invasion (LVI) and support more tailored treatment strategies.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How were biomarkers selected to build the G-Risk scoring system?",{"text":118,"@type":114},"Key biomarkers linked to survival outcomes were identified using univariate and multivariate Cox regression analyses, selected from inflammatory and tumor markers to construct the scoring system.",{"name":120,"@type":111,"acceptedAnswer":121},"What were the key findings regarding predictive performance?",{"text":122,"@type":114},"The G-Risk score stratified patients into high-risk and low-risk groups with an AUC of 0.660, and further multivariate analysis validated it as an independent prognostic factor for patient survival.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},369406,1790642729,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":135,"file_id":136,"file_url":137,"file_type":138,"file_size":139,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":105,"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},2336474466412,"https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d","Liu et al. European Journal  \nEuropean Journal of Medical Research (2025) 30:308  \n[https://doi.org/10.1186/s40001-025-02540-4](https://doi.org/10.1186/s40001-025-02540-4 of Medical Research)[ of Medical Research](https://doi.org/10.1186/s40001-025-02540-4 of Medical Research)  \n RESEARCH Open Access  \nDevelopment of the G-Risk scoring system   utilizing inflammatory and tumor biomarkers to improve prognostic accuracy in gastric cancer patients without lymphovascular invasion  \nEryu Liu1†, Boran Xu1†, Lei Shi1, Huannan Guo1, Chunfeng Li2* and Lili Lv 1*  \nAbstract  \nObjective This study aimed to establish the G-Risk scoring system, a prognostic model based on inflammatory and tumor biomarkers, to enhance survival predictions for gastric cancer patients without lymphovascular invasion (LVI) and guide more tailored treatment strategies.  \nMethods The key biomarkers associated with survival outcomes were identified using univariate and multivariate Cox regression analyses. These biomarkers were selected from a range of inflammatory and tumor markers to construct the G-Risk scoring system, which was specifically developed to improve prognostic accuracy in patients without LVI.  \nResults The G-Risk score effectively stratified patients into high-risk and low-risk groups, achieving an AUC of 0 . 660, demonstrating strong predictive performance. Further multivariate analysis validated the G-Risk score as an independent prognostic factor with significant implications for patient survival.  \nConclusion The G-Risk score was successfully developed and validated as a reliable prognostic tool for gastric cancer patients without LVI. Its clinical implementation offers enhanced precision in assessing prognostic risk, facilitating personalized treatment planning, improving therapeutic outcomes, and reducing unnecessary medical interventions. Keywords Gastric cancer, Prognosis, Lymphovascular invasion  \nIntroduction  \nGastric cancer remains a significant health burden globally, particularly in parts of East Asia, Eastern Europe, and South America, where incidence and mortality rates  \n†Eryu Liu and Boran Xu have contributed equally to this work.  \n*Correspondence:  \nChunfeng Li[lichunfeng007@hrbmu.edu.cn](lichunfeng007@hrbmu.edu.cn)[ ](lichunfeng007@hrbmu.edu.cn)Lili Lv  \n[155398919@qq.com](155398919@qq.com)  \n1 Department of Oncology, Beidahuang Industry Group General Hospital, Harbin, China  \n2 Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital, Harbin, China  \nare high [1]. According to global cancer statistics, gastric cancer is the fifth most common cancer worldwide and the fourth leading cause of cancer death [2]. Often diagnosed at a late stage, the complexity and limited options for treatment highlight the importance of accurately predicting disease progression and patient prognosis [3, 4]. In the treatment and prognosis assessment of gastric cancer, specific biomarkers and clinical features are used to evaluate the disease’s aggressiveness and expected outcomes, among which lymphovascular invasion (LVI) is a key factor [5, 6].  \nLVI is considered a poor prognostic biomarker in gastric cancer, typically associated with higher recurrence rates and lower survival rates. Compared to patients with  \n© The Author(s) 2025. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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. I","cbCaiqu3GZq0NAfU","https://ap.wps.com/l/cbCaiqu3GZq0NAfU","pdf",2259253,"English","# Abstract\n# Introduction\n## Burden of gastric cancer\n## Role of lymphovascular invasion (LVI)\n## Inflammation and biomarker rationale\n# Methods\n# Results\n# Conclusion","[{\"question\":\"What is the main objective of the study?\",\"answer\":\"The study aims to establish the G-Risk scoring system to enhance prognostic accuracy for gastric cancer patients without lymphovascular invasion (LVI) and support more tailored treatment strategies.\"},{\"question\":\"How were biomarkers selected to build the G-Risk scoring system?\",\"answer\":\"Key biomarkers linked to survival outcomes were identified using univariate and multivariate Cox regression analyses, selected from inflammatory and tumor markers to construct the scoring system.\"},{\"question\":\"What were the key findings regarding predictive performance?\",\"answer\":\"The G-Risk score stratified patients into high-risk and low-risk groups with an AUC of 0.660, and further multivariate analysis validated it as an independent prognostic factor for patient survival.\"}]","Development of the G-Risk scoring system - utilizing inflammatory and tumor biomarkers to improve prognostic accuracy in gastric cancer patients without lymphovascular invasion | PDF",1790182451,28]