[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127536-en":3,"doc-seo-127536-105":31,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},127536,687207017582,"Himbo","https://ap-avatar.wpscdn.com/davatar_994ba38a5ba835b3df7d355c54d3ed8d",8,"Research & Report","An online survival predictor in glioma patients using machine learning based on WHO CNS5 data","An online prognostic model for glioma patients is developed using machine learning and WHO CNS5–related biomarkers. Patient data spanning 2011–2022 are extracted from a clinical database, then divided into training and hold-out test sets. A WHO CNS5-associated risk signature and nomogram are constructed with RF, SVM, XGB, and GLM, followed by ROC, calibration, and decision-curve evaluations. The resulting tool, implemented as an online calculator, estimates individualized survival probabilities and demonstrates predictive discrimination and calibration across 1-, 3-, and 5-year outcomes.","TYPE Original Research PUBLISHED 19 May 2023  \nDOI 10.3389/fneur.2023.1179761  \nOPEN ACCESS  \nEDITED BY  \nWei Zhao,  \nBeihang University, China  \nREVIEWED BY  \nYun Qin,  \nBeihang University, China Shijia Wang,  \nHunan University, China  \n*CORRESPONDENCE  \nYu Wang  \n [ywang@pumch.cn](ywang@pumch.cn)[ ](ywang@pumch.cn)Wenbin Ma  \n [mawb2001@hotmail.com](mawb2001@hotmail.com)  \n†These authors have contributed equally to this work  \nRECEIVED 08 March 2023  \nACCEPTED 25 April 2023  \nPUBLISHED 19 May 2023  \nCITATION  \nYe L, Gu L, Zheng Z, Zhang X, Xing H, Guo X, Chen W, Wang Y, Wang Y, Liang T, Wang H, Li Y, Jin S, Shi Y, Liu D, Yang T, Liu Q, Deng C, Wang Y and Ma W (2023) An online survival predictor in glioma patients using machine learning based on WHO CNS5 data.  \nFront. Neurol. 14:1179761 .  \ndoi: 10.3389/fneur.2023.1179761  \nCOPYRIGHT  \n© 2023 Ye, Gu, Zheng, Zhang, Xing, Guo, Chen, Wang, Wang, Liang, Wang, Li, Jin, Shi, Liu, Yang, Liu, Deng, Wang and Ma. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nAn online survival predictor in glioma patients using machine learning based on WHO CNS5 data  \nLiguo Ye 1†, Lingui Gu 1†, Zhiyao Zheng 1, 2, 3†, Xin Zhang 1†, Hao Xing 1†, Xiaopeng Guo 1, 4†, Wenlin Chen 1†, Yaning Wang 1, Yuekun Wang 1, Tingyu Liang 1, Hai Wang 1, Yilin Li 1, 5, Shanmu Jin 1, 5, Yixin Shi 1, 6, Delin Liu 1, 6, Tianrui Yang 1, 6, Qianshu Liu 1, 6, Congcong Deng 1, Yu Wang 1, 4* and Wenbin Ma 1, 4*  \n1 Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT Alliance, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 2 Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China, 3 Research Unit of Accurate Diagnosis, Treatment, and Translational Medicine of Brain Tumors (No. 2019RU011), Chinese Academy of Medical Sciences, Beijing, China, 4China AntiCancer Association Specialty Committee of Glioma, Beijing, China, 54+4 Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China, 6 Eight-year Medical Doctor Program, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China  \nBackground: The World Health Organization (WHO) CNS5 classification system highlights the significance of molecular biomarkers in providing meaningful prognostic and therapeutic information for gliomas. However, predicting individual patient survival remains challenging due to the lack of integrated quantitative assessment tools. In this study, we aimed to design a WHO CNS5-related risk signature to predict the overall survival (OS) rate of glioma patients using machine learning algorithms.  \nMethods: We extracted data from patients who underwent an operation for histopathologically confirmed glioma from our hospital database (2011–2022) and split them into a training and hold-out test set in a 7/3 ratio. We used biological markers related to WHO CNS5, clinical data (age, sex, and WHO grade), and prognosis follow-up information to identify prognostic factors and construct a predictive dynamic nomograph to predict the survival rate of glioma patients using 4 kinds machine learning algorithms (RF, SVM, XGB, and GLM) .  \nResults: A total of 198 patients with complete WHO5 molecular data and followup information were included in the study. The median OS time of all patients was 29.77 [95% confidence interval (CI): 21.19–38.34] months. Age, FGFR2, IDH1, CDK4, CDK6, KIT, and CDKN2A were considered vital indicators related to the prognosis and","cbCaiqUWU5Nrhal5","https://ap.wps.com/l/cbCaiqUWU5Nrhal5","pdf",5214014,2,1,15,"English","en",105,"# Background\n# Methods\n## Data extraction and cohorts\n## Model building and algorithms\n# Results\n## Patient characteristics and survival metrics\n## Risk signature and nomogram performance\n## Validation and clinical utility\n# Conclusion","[{\"question\":\"What is the goal of the study on glioma survival prediction?\",\"answer\":\"To design a WHO CNS5-related risk signature and an online predictor that estimates overall survival for individual glioma patients using machine learning.\"},{\"question\":\"Which patient data and WHO CNS5–related variables are used to build the model?\",\"answer\":\"The study uses biological markers related to WHO CNS5, clinical data such as age, sex, and WHO grade, and follow-up prognosis information.\"},{\"question\":\"How does the online survival predictor evaluate performance and reliability?\",\"answer\":\"Model quality is assessed using ROC curves for 1-, 3-, and 5-year survival, calibration plots, and c-index values, with decision curve analysis supporting net clinical benefit.\"}]","An online survival predictor in glioma patients using machine learning based on WHO CNS5 data | PDF",1785939821,38,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":29},"an-online-survival-predictor-in-glioma-patients-using-machine-learning-based-on-who-cns5-data","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,48,51],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":20},"https://docshare.wps.com/document/","Document",{"item":49,"name":12,"@type":44,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":44,"position":53},"https://docshare.wps.com/document/an-online-survival-predictor-in-glioma-patients-using-machine-learning-based-on-who-cns5-data/127536/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":24,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":42,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-22","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What is the goal of the study on glioma survival prediction?","Question",{"text":76,"@type":77},"To design a WHO CNS5-related risk signature and an online predictor that estimates overall survival for individual glioma patients using machine learning.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which patient data and WHO CNS5–related variables are used to build the model?",{"text":81,"@type":77},"The study uses biological markers related to WHO CNS5, clinical data such as age, sex, and WHO grade, and follow-up prognosis information.",{"name":83,"@type":74,"acceptedAnswer":84},"How does the online survival predictor evaluate performance and reliability?",{"text":85,"@type":77},"Model quality is assessed using ROC curves for 1-, 3-, and 5-year survival, calibration plots, and c-index values, with decision curve analysis supporting net clinical benefit.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":93},[94,98,102,106,111,116,121,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":47,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":47,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]