{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T14:26:57Z","timestamp":1787495217727,"version":"build-2736575974"},"reference-count":36,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T00:00:00Z","timestamp":1767830400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Nutr."],"abstract":"\n Background<\/jats:title>\n The cachexia index (CXI) has emerged as a recognized prognostic biomarker of cancer cachexia. However, the dynamic progression of cachexia may not be fully captured by a single assessment. This study examined the impact of integrating the CXI with BMI trajectories on the survival prognosis of patients with cancer cachexia to enable early identification of high-risk populations.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n This is a retrospective review of clinical and pathological data from 147 patients diagnosed with cancer cachexia at Xuzhou Central Hospital between January 2019 and May 2024. Based on computed tomography images at the time of initial cancer cachexia diagnosis to calculate the L3-SMI, the CXI was calculated using serum albumin (ALB) level, neutrophil-to-lymphocyte ratio (NLR), and skeletal muscle index (SMI). Using X-tile software, gender-specific optimal cutoff values for CXI were determined, and patients were divided into low and high CXI groups. Multiple BMI measurements were collected, and BMI dynamic trajectory subtypes were identified using latent category growth mixture modeling (GMM). Cox regression analysis was performed to identify independent risk factors for overall survival (OS); Kaplan\u2013Meier survival curves were plotted; and subgroup interactions were analyzed according to cancer type, BMI trajectory subtype, ECOG PS, and TNM stage. A heterogeneity analysis of CT-based body composition was conducted to evaluate the relationship between muscle and adipose tissue.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n GMM revealed two types of BMI decline trajectories: Class 1 (low reserve-slow decline BMI, 58%) and Class 2 (high reserve-accelerated decline BMI, 42%). The low CXI group had a considerably shorter median OS compared to the high CXI group (4.5 vs. 8.3\u2009months,\n p<\/jats:italic>\n \u2009&lt;\u20090.001), with the low CXI and Class 1 subgroup having the poorest prognosis (median OS 3.5\u2009months vs. other subgroups,\n p<\/jats:italic>\n \u2009&lt;\u20090.001). Multivariate Cox regression analysis identified low CXI, ECOG PS 2\u20133, and TNM Stage III-IV as independent risk factors for OS (\n p<\/jats:italic>\n \u2009&lt;\u20090.05). Subgroup analysis showed that low CXI significantly increased the risk of death in patients with gastrointestinal cancer, Class 1, and TNM Stage III-IV (\n p<\/jats:italic>\n \u2009&lt;\u20090.05), and there was no interaction with cancer type, BMI trajectory subtype, ECOG PS, or TNM Stage (\n p<\/jats:italic>\n \u2009&gt;\u20090.05). The third lumbar spinal muscle area (L3-SMA) was weakly positively correlated with subcutaneous fat thickness (SFT) (Spearman\n r<\/jats:italic>\n \u2009=\u20090.256,\n p<\/jats:italic>\n \u2009=\u20090.0018).\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n The combination of low CXI and Class 1 trajectory was identified as an exceedingly high-risk phenotype with markedly poor survival, mandating early intensive intervention. This novel composite model provides a critical foundation for early risk stratification and precise intervention strategies in cancer cachexia, with the potential to significantly improve patient prognosis.<\/jats:p>\n <\/jats:sec>","DOI":"10.3389\/fnut.2025.1706391","type":"journal-article","created":{"date-parts":[[2026,1,8]],"date-time":"2026-01-08T05:12:06Z","timestamp":1767849126000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["The impact of cachexia index combined with BMI trajectory on survival outcomes in patients with cancer cachexia"],"prefix":"10.3389","volume":"12","author":[{"given":"Xue","family":"Cheng","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lijuan","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junhao","family":"Ren","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaying","family":"Mo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qing","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,1,8]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1016\/S1470-2045(10)70218-7","article-title":"Definition 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