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This study evaluated systemic immunoinflammatory index (SII) and CT-derived body composition parameters to predict CRS severity in 45 advanced gastric cancer patients treated with CLDN18.2-targeted CAR-T cells. Automated deep learning segmentation quantified baseline waist, SMI, SMD, SFA, VFA, and VFA-to-SFA ratio (VSR), followed by ROC analysis and univariate/multivariate logistic regression. VSR and SII were higher in CRS grade 2, and SII and VSR thresholds supported high-grade CRS prediction.",{"@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":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/a-two-step-scoring-model-incorporating-visceral-to-subcutaneous-fat-ratio-and-systemic-immunoinflammatory-index/356458/",{"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/a-two-step-scoring-model-incorporating-visceral-to-subcutaneous-fat-ratio-and-systemic-immunoinflammatory-index/356458.png","ImageObject",300,407,{"name":92,"@type":93},"River Wang","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-11-02","2026-09-23",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What clinical factor was used to predict CRS severity in this study?","Question",{"text":112,"@type":113},"The study assessed the systemic immunoinflammatory index (SII) and CT-derived body composition parameters, especially the visceral-to-subcutaneous fat area ratio (VSR), to predict CRS severity.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How were the body composition parameters obtained?",{"text":117,"@type":113},"Baseline CT images were automatically segmented and used to calculate waist circumference, skeletal muscle index (SMI), skeletal muscle density (SMD), subcutaneous fat area (SFA), visceral fat area (VFA), and VFA-to-SFA ratio (VSR) using a deep learning-based tool.",{"name":119,"@type":110,"acceptedAnswer":120},"What were the key findings distinguishing CRS grade 1 from grade 2?",{"text":121,"@type":113},"CRS grade 2 showed significantly higher VSR and SII than CRS grade 1, while SMI, SMD, SFA, and waist circumference did not differ significantly.","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},356458,1790182443,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":34,"category_name":35,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"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},1099514067438,"https://ap-avatar.wpscdn.com/avatar/100002539ee87300030?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780474512215547542","Cancer Immunology, Immunotherapy (2026) 75:96  \n[https://doi.org/10.1007/s00262-026-04341-y](https://doi.org/10.1007/s00262-026-04341-y)  \nA two‑step scoring model incorporating visceral‑to‑subcutaneous fat ratio and systemic immunoinflammatory index for predicting cytokine release syndrome severity in patients with gastric cancer receiving  \nClaudin18.2‑targeted CAR‑T cell therapy  \nMeng He1 · Lian Liu2 · Zifan Chen3 · Yiting Liu1 · Chang Liu4 · Mingyang Ma2 · Jiarui Li2 · Bin Dong5,6,7 · Jifang Gong8 · Lin Shen8 · Lei Tang1 · Changsong Qi9  \nReceived: 7 April 2025 / Accepted: 15 February 2026 © The Author(s) 2026  \nAbstract  \nCytokine release syndrome (CRS) greatly impacts survival in patients who undergo chimeric antigen receptor (CAR)-T cell therapy, and the identification of its determinants is still challenging. We analysed the impact of systemic immunoinflammatory index (SII) and body composition parameters derived from CT images on the severity of CRS in 45 patients with advanced gastric cancer treated with CLDN18.2-targeted CAR-T cells. The waist circumference, skeletal muscle index (SMI), skeletal muscle density (SMD), subcutaneous fat area (SFA), visceral fat area (VFA) and VFA-to-SFA ratio (VSR) on baseline CT were automatically segmented and calculated using a deep learning-based tool. The relationship between SII, body composition, and CRS severity was investigated by using ROC analysis, univariate and multivariate binary logistic regression. There were no significant differences in SMI, SMD, SFA and waist circumference between patients with CRS grade 1 and 2. CRS grade 2 patients exhibited significantly higher VSR and SII than patients with CRS grade 1 (P = 0.003 and 0.012, respectively). ROC analysis showed that the AUCs of VSR and SII for predicting CRS grade were 0.762 (0.620–0.905) and 0.721 (0 .563–0. 879), respectively. Logistic regression analysis demonstrated that SII > 553 × 109/L and VSR ≥ 0.21 were significantly linked with high grade CRS (P = 0.035 and 0.014, respectively). We constructed a two-step scoring CRS prediction model based on VSR and SII, and the AUC of this model achieved 0.802 (0.665–0.939) for predicting high-grade CRS in advanced gastric cancer patients receiving CLDN18.2-targeted CAR-T cell therapy, providing a practical tool for early risk stratification and clinical intervention.  \nKeywords Chimeric antigen receptor-T cell therapy · Cytokine release syndrome · Body composition parameters · Nutritional status  \nAbbreviations  \nAUC The area under the ROC curve  \nCAR-T Chimeric antigen receptor-T  \nCLDN18 .2 Claudin18 .2  \nCRP C-reactive protein  \nCRS Cytokine release syndrome  \nECOG Eastern cooperative oncology group  \nGC Gastric cancer  \nL3 The third lumbar vertebra  \nSAT Subcutaneous adipose tissue  \nMeng He, Lian Liu and Zifan Chen have contributed equally to this work.  \nExtended author information available on the last page of the article  \nSFA Subcutaneous fat area  \nSII Systemic immunoinflammatory index  \nSMD Skeletal muscle density  \nSMI Skeletal muscle index  \nVAT Visceral adipose tissue  \nVFA Visceral fat area  \nVSR VFA-to-SFA ratio  \nIntroduction  \nCAR-T cell therapy is gaining momentum as a treatment option [1] . Compared with conventional immunotherapy, CAR-T cells can significantly proliferate and kill tumour cells in vivo upon antigen engagement, leading  \nto a breakthrough in therapeutic efficacy [2, 3] . However, adverse events associated with CAR-T cell therapy are also evident [4] . The activation and expansion of CAR-T cells precipitate a surge in cytokine production, thus triggering an elevated systemic inflammatory response, which may lead toa range of clinical symptoms, such as fever, hypotension and hypoxia [5]. Treatment for cytokine release syndrome (CRS) is generally controllable, and the IL-6 receptor inhibitor tocilizumab can be used preemptively to prevent toxicity after infusion [6]; moreover, oxygen and vasoactive medications may ameliorate severe CRS. ","cbCaicg8gtgG1ebT","https://ap.wps.com/l/cbCaicg8gtgG1ebT","pdf",2294105,14,"English","# Abstract\n## Keywords\n## Abbreviations\n## Introduction","[{\"question\":\"What clinical factor was used to predict CRS severity in this study?\",\"answer\":\"The study assessed the systemic immunoinflammatory index (SII) and CT-derived body composition parameters, especially the visceral-to-subcutaneous fat area ratio (VSR), to predict CRS severity.\"},{\"question\":\"How were the body composition parameters obtained?\",\"answer\":\"Baseline CT images were automatically segmented and used to calculate waist circumference, skeletal muscle index (SMI), skeletal muscle density (SMD), subcutaneous fat area (SFA), visceral fat area (VFA), and VFA-to-SFA ratio (VSR) using a deep learning-based tool.\"},{\"question\":\"What were the key findings distinguishing CRS grade 1 from grade 2?\",\"answer\":\"CRS grade 2 showed significantly higher VSR and SII than CRS grade 1, while SMI, SMD, SFA, and waist circumference did not differ significantly.\"}]","A two-step scoring model incorporating visceral-to-subcutaneous fat ratio and systemic immunoinflammatory index | PDF",1790125412,35]