[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128258-en":3,"doc-seo-128258-105":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},128258,2336475104736,"Quinn","https://ap-avatar.wpscdn.com/avatar/22000c4c5e0e5b17e70?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786591360781797222",8,"Research & Report","Quality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancer - Research report","Integrative machine learning uses diverse patient-reported quality-of-life (QoL) scales to anticipate outcomes for advanced non-small cell lung cancer patients treated with atezolizumab. Baseline QoL is linked to clinical endpoints across four randomized clinical trials, with discovery driven by consensus clustering to derive quality-of-life subtypes and validation performed in external cohorts. One subtype shows significantly poorer overall and progression-free survival and reduced clinical benefit, while the other subtype supports atezolizumab efficacy versus chemotherapy.","TYPE Original Research PUBLISHED 18 July 2025  \nDOI 10.3389/fimmu.2025.1600265  \nOPEN ACCESS  \nEDITED BY  \nZodwa Dlamini,  \nPan African Cancer Research Institute (PACRI), South Africa  \nREVIEWED BY  \nPalash Mandal,  \nCharotar University of Science and Technology, India  \nMansoor-Ali Vaali-Mohammed, King Saud University, Saudi Arabia Yunpeng Hua,  \nThe First Affiliated Hospital of Sun Yat-sen University, China  \nDia Roy,  \nCleveland Clinic, United States  \n*CORRESPONDENCE  \nJunliang Ma  \n [majunliang2021@sina.com](majunliang2021@sina.com)[ ](majunliang2021@sina.com)Hu Ma  \n [mahuab@163.com](mahuab@163.com)[ ](mahuab@163.com)Jian-Guo Zhou  \n[jianguo.zhou@zmu.edu.cn](jianguo.zhou@zmu.edu.cn)  \n†These authors have contributed equally to this work  \nRECEIVED 23 April 2025  \nACCEPTED 26 June 2025  \nPUBLISHED 18 July 2025  \nCITATION  \nShen J, Ma J, Chen S, Jin S-H, Xu J, Li Q, Zhang C, Tian X, Chen X, Tan F, Hecht M, Frey B, Gaipl US, Ma H and Zhou J-G (2025)  \nQuality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancer.  \nFront. Immunol. 16:1600265 .  \ndoi: 10.3389/fimmu.2025.1600265  \nCOPYRIGHT  \n© 2025 Shen, Ma, Chen, Jin, Xu, Li, Zhang, Tian, Chen, Tan, Hecht, Frey, Gaipl, Ma and Zhou. 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.  \nQuality-of-life scale machine learning approach to predict immunotherapy response inpatients with advanced nonsmall cell lung cancer  \nJuanyan Shen 1,2,3†, Junliang Ma 3*, Shaolin Chen 4†, Su-Han Jin 5, Junzhu Xu 1, Qisha Li 1, Chi Zhang 1, Xiaojing Tian 1,  \nXiaofei Chen 6, Fangya Tan 7, Markus Hecht 8, Benjamin Frey 9,10,11, Udo S. Gaipl 9,10,11, Hu Ma 1* and Jian-Guo Zhou 1,8,12*  \n1 Department of Oncology, The Second Affiliated Hospital of Zunyi Medical University, Zunyi, China, 2 Department of Thoracic Surgery, The Third Affiliated Hospital of Zunyi Medical University, The First People's Hospital of Zunyi, Zunyi, Guizhou, China, 3 Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China, 4 Nursing Department, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, China, 5 Department of Orthodontics, Affiliated Stomatological Hospital of Zunyi Medical University, Zunyi, China, 6Oncology Biometrics, AstraZeneca, Gaithersburg, MD, United States, 7 Harrisburg University of Science and Technology, Harrisburg, PA, United States, 8 Department of Radiotherapy and Radiation Oncology, Saarland University Medical Center, Homburg, Germany, 9Translational Radiobiology, Department of Radiation Oncology, Universitätsklinikum Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 10Comprehensive Cancer Center Erlangen-Europäische Metropolregion Nürnberg (EMN), Erlangen, Germany, 11 Friedrich-Alexander-Universität (FAU) Profile Center Immunomedicine (FAU I-MED), Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany, 12 Department of Biostat and Programming, Sanofi, Bridgewater, NJ, United States  \nBackground: Despite immune checkpoint inhibitors(ICIs) significantly improve clinical outcomes in patients with advanced non-small cell lung cancer (aNSCLC), disease progression is inevitable. A diverse patient-reported Qualityof-life(QoL) scales were used to predict outcomes for aNSCLC patients with atezolizumab using machine learning.  \nMaterials and Methods: This study analyzed the association between baseline QoL and clinical outcomes in aNSCLC patients with atezolizumab in 4 randomized clinical trials: the IMpower150 study (discovery cohort), the BIRCH, OAK an","cbCaimhlY1IB0L2U","https://ap.wps.com/l/cbCaimhlY1IB0L2U","pdf",10472855,4,1,13,"English","en",105,"# Background\n## Immune checkpoint inhibitor limitations and resistance\n# Materials and Methods\n## Data sources from randomized clinical trials\n## Consensus clustering and external validation\n# Results\n## Quality-of-life subtypes and survival associations\n## Treatment benefit differences\n# Conclusions\n## Predictive value of machine learning on baseline QoL","[{\"question\":\"What clinical problem does the study address in advanced NSCLC immunotherapy?\",\"answer\":\"Disease progression remains inevitable for advanced non-small cell lung cancer patients despite immune checkpoint inhibitor benefits. The study targets the need to identify patients most likely to achieve meaningful and sustained control.\"},{\"question\":\"How were quality-of-life subtypes derived and tested?\",\"answer\":\"Quality-of-life subtypes were identified using consensus clustering in the discovery cohort. The predicted subtypes were then assessed in external validated cohorts drawn from multiple randomized clinical trials.\"},{\"question\":\"What do the identified QoL subtypes imply for treatment outcomes?\",\"answer\":\"One QoL subtype (QoLS2) is associated with worse overall survival and progression-free survival and lower clinical benefit, while the other subtype (QoLS1) behaves as a positive predictive marker of atezolizumab efficacy compared with chemotherapy.\"}]","Quality-of-life scale machine learning approach to predict immunotherapy response in patients with advanced non-small cell lung cancer - Research report | PDF",1785946279,33,{"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},"quality-of-life-scale-machine-learning-approach-to-predict-immunotherapy-response-in-patients-with-advanced-non-small-cell-lung-cancer-research-report","",{"@graph":37,"@context":86},[38,54,69],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/research-report/",3,{"item":53,"name":13,"@type":44,"position":20},"https://docshare.wps.com/document/quality-of-life-scale-machine-learning-approach-to-predict-immunotherapy-response-in-patients-with-advanced-non-small-cell-lung-cancer-research-report/128258/",{"url":53,"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","2026-08-27","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 clinical problem does the study address in advanced NSCLC immunotherapy?","Question",{"text":76,"@type":77},"Disease progression remains inevitable for advanced non-small cell lung cancer patients despite immune checkpoint inhibitor benefits. The study targets the need to identify patients most likely to achieve meaningful and sustained control.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"How were quality-of-life subtypes derived and tested?",{"text":81,"@type":77},"Quality-of-life subtypes were identified using consensus clustering in the discovery cohort. The predicted subtypes were then assessed in external validated cohorts drawn from multiple randomized clinical trials.",{"name":83,"@type":74,"acceptedAnswer":84},"What do the identified QoL subtypes imply for treatment outcomes?",{"text":85,"@type":77},"One QoL subtype (QoLS2) is associated with worse overall survival and progression-free survival and lower clinical benefit, while the other subtype (QoLS1) behaves as a positive predictive marker of atezolizumab efficacy compared with chemotherapy.","https://schema.org",{"og:url":53,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":53},"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":48,"doc_module":4,"doc_module_name":47,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":20,"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"]