[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-seo-357729-105":3,"detail-sidebar-cat-0-en-105":81,"doc-detail-357729-en":130},{"code":4,"msg":5,"data":6},0,"ok",{"site_id":7,"language":8,"slug":9,"title":10,"keywords":11,"description":12,"schema_data":13,"social_meta":74,"head_meta":76,"extra_data":78,"updated_unix":80},105,"en","long-term-stability-of-the-triglyceride-glucose-index-in-cancer-patient-cohort","Long-term stability of the triglyceride-glucose index in cancer patient cohort","","The triglyceride-glucose (TyG) index serves as a simple surrogate marker for insulin resistance, yet its longitudinal stability and clinical predictive value in cancer patients have been unclear. This retrospective single-center cohort study included 538 cancer patients (2015–2020) with five TyG index measurements over 24 months. Repeated-measures analysis and intraclass correlation quantified stability, while logistic regression and longitudinal K-means clustering assessed influencing factors and trajectory patterns. TyG showed excellent stability over 24 months, with BMI as the independent driver of higher TyG levels.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/healthcare/","Healthcare",3,{"item":32,"name":10,"@type":21,"position":33},"https://docshare.wps.com/document/long-term-stability-of-the-triglyceride-glucose-index-in-cancer-patient-cohort/357729/",4,{"url":32,"name":10,"@type":35,"image":36,"author":41,"headline":10,"publisher":44,"fileFormat":47,"inLanguage":8,"description":12,"dateModified":48,"datePublished":49,"encodingFormat":47,"isAccessibleForFree":50,"interactionStatistic":51},"DigitalDocument",{"url":37,"@type":38,"width":39,"height":40},"https://docshare.wps.com/thumbnails/long-term-stability-of-the-triglyceride-glucose-index-in-cancer-patient-cohort/357729.png","ImageObject",300,407,{"name":42,"@type":43},"awa","Person",{"url":19,"name":45,"@type":46},"DocShare","Organization","application/pdf","2026-11-03","2026-09-23",true,{"@type":52,"interactionType":53,"userInteractionCount":55},"InteractionCounter",{"@type":54},"ViewAction",8,{"@type":57,"mainEntity":58},"FAQPage",[59,65,69],{"name":60,"@type":61,"acceptedAnswer":62},"What was the main objective of the study?","Question",{"text":63,"@type":64},"To determine whether cancer and anti-tumor therapies influence the 24-month longitudinal stability of the TyG index and to identify its key influencing factors.","Answer",{"name":66,"@type":61,"acceptedAnswer":67},"How was TyG index stability evaluated over time?",{"text":68,"@type":64},"Longitudinal stability was quantified using repeated measures analysis of variance (RMANOVA) and intraclass correlation coefficients (ICC) across five measurements over 24 months.",{"name":70,"@type":61,"acceptedAnswer":71},"Which factor was independently associated with a high TyG index?",{"text":72,"@type":64},"Body mass index (BMI) was identified as the core factor independently associated with a high TyG index.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},357729,1790472256,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,114,119,122,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & Novel",90,"story-novel",{"id":26,"doc_module":4,"doc_module_name":25,"category_name":89,"show_sort_weight":90,"slug":91},"Literature",80,"literature",{"id":33,"doc_module":4,"doc_module_name":25,"category_name":93,"show_sort_weight":94,"slug":95},"Exam",70,"exam",{"id":97,"doc_module":4,"doc_module_name":25,"category_name":98,"show_sort_weight":99,"slug":100},5,"Comic",60,"comic",{"id":102,"doc_module":4,"doc_module_name":25,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":25,"category_name":29,"show_sort_weight":108,"slug":109},7,40,"healthcare",{"id":55,"doc_module":4,"doc_module_name":25,"category_name":111,"show_sort_weight":112,"slug":113},"Research & Report",30,"research-report",{"id":115,"doc_module":4,"doc_module_name":25,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":25,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":25,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":25,"category_name":128,"show_sort_weight":97,"slug":129},19,"General","general",{"code":4,"msg":82,"data":131},{"doc_id":79,"user_id":132,"nickname":42,"user_avatar":133,"doc_module":4,"category_id":107,"category_name":29,"doc_title":10,"doc_description":12,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":55,"is_deleted":4,"is_public":22,"is_downloadable":22,"audit_status":22,"page_count":115,"language":139,"language_code":8,"site_id":7,"html_lang":8,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":12,"update_tm":143,"read_time":144},3985747858093,"https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2","[www. nature.com/scientificreports](www. nature.com/scientificreports)  \nOPEN  \nLong-term stability of the triglyceride-glucose index in cancer patient Cohort  \nYuleiXie, XinChen, Liang Xie & Yinxu Wang􀀍  \nThe triglyceride-glucose (TyG) index is a simple surrogate marker for insulin resistance (IR), but its longitudinal stability and clinical predictive value in patients with cancer remain poorly understood. To evaluate whether cancer and anti-tumor therapies affect the longitudinal stability oftheTyG index over 24 months and to identify its core influencing factors. This retrospective study analyzed 538 cancer patients from a single-center database (2015–2020) who completed five TyG index measurements over 24 months. Longitudinal stability was quantified using repeated measures analysis of variance (RMANOVA) and intraclass correlation coefficients (ICC). Binary logistic regression models were employed to explore factors associated with different TyG levels. A longitudinal K-means clustering algorithm was used to identify trajectory differences, and multivariable logistic regression models determined the independent predictive factors. The TyG index demonstrated excellent longitudinal stability over 24 months (F = 5.38, P \u003C 0.001; average ICC = 0.890; Pearson r = 0.54–0.71). Binary logistic regression analysis showed that body mass index (BMI) was the core factor independently associated with a high TyG index (Q4 > 8.79). K-means clustering identified three parallel longitudinal trajectories (StableLow, Stable-Medium, and Stable-High risk) . Multivariable logistic regression models indicated that the high-risk trajectory was significantly associated with BMI (OR = 1.25, 95% CI 1.10–1.41, P \u003C 0.001) and diabetes mellitus, whereas advanced cancer stage (OR = 0.95, 95% CI 0.53–1.70, P = 0.862) and cachexia (OR = 0.90, 95% CI 0.45–1.80, P = 0.767) showed no significant effect. The TyG index in cancer patients exhibited a long-term stable trend over 24 months. Severe IR may represent a metabolic phenotype closely associated with fat accumulation, and it may be independent of catabolic states such as cancer stage and cachexia.  \nKeywords insulin resistance, triglyceride-glucose index, cancer, diabetes mellitus, longitudinal cohort, predictive model  \nThe triglyceride-glucose (TyG) index, as a simple and highly sensitive surrogate marker for insulin resistance (IR), has been widely recognized for its predictive value in cardiovascular and metabolic diseases1–3. However, the hyperinsulinemic-euglycemic clamp test, considered the gold standard for assessing IR, is difficult to apply rapidly in large-scale clinical cohorts due to its complexity and high cost4,5. As a potential diagnostic tool, the TyG index only requires the calculation of fasting triglycerides (TG) and fasting plasma glucose (FPG), offering the advantages of convenience and low cost6,7. Recent studies have shown that the TyG index is not only associated with systemic IR and hyperinsulinemia but also plays a role in oncogenic pathways via insulin-related receptors (such as IGF-1, PI3K, and Akt)8,9.  \nHowever, current research on the TyG index in the cancer field still has significant limitations: it relies mostly on single baseline measurements. In reality, the disease trajectory of cancer is complex and accompanied by abnormal physiological and metabolic fluctuations10. On the one hand, the high-consumption state of cancer (such as cachexia) can induce catabolism and malnutrition; on the other hand, frequent iatrogenic interventions (such as chemoradiotherapy and metabolic drugs) may disrupt lipid homeostasis11. In this environment of physiological stress and cancer burden, exploring the reliability of the TyG index in cancer metabolic monitoring and assessing its long-term longitudinal stability is of great clinical value.  \nThis study longitudinally evaluated the stability of the TyG index in cancer participants over 24 months. It also aimed to analyze the independen","cbCaiu6qKmpT1Pcq","https://ap.wps.com/l/cbCaiu6qKmpT1Pcq","pdf",2014076,"English","# Materials and methods\n## Participants\n## TyG definition and laboratory measurements\n## Included variables\n## Sample size calculation","[{\"question\":\"What was the main objective of the study?\",\"answer\":\"To determine whether cancer and anti-tumor therapies influence the 24-month longitudinal stability of the TyG index and to identify its key influencing factors.\"},{\"question\":\"How was TyG index stability evaluated over time?\",\"answer\":\"Longitudinal stability was quantified using repeated measures analysis of variance (RMANOVA) and intraclass correlation coefficients (ICC) across five measurements over 24 months.\"},{\"question\":\"Which factor was independently associated with a high TyG index?\",\"answer\":\"Body mass index (BMI) was identified as the core factor independently associated with a high TyG index.\"}]","Long-term stability of the triglyceride-glucose index in cancer patient cohort | PDF",1790131558,23]