Synergic value of 3D CT-derived body composition and triglyceride glucose body mass for survival prognostic modeling in unresectable pancreatic cancer.
Kangjing Xu, Xinbo Wang, Changsheng Zhou, Junbo Zuo, Chenghao Zeng, Pinwen Zhou, Li Zhang, Xuejin Gao, Xinying Wang
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引用次数: 0
Abstract
Background: Personalized and accurate survival risk prognostication remains a significant challenge in advanced pancreatic ductal adenocarcinoma (PDAC), despite extensive research on prognostic and predictive markers. Patients with PDAC are prone to muscle loss, fat consumption, and malnutrition, which is associated with inferior outcomes. This study investigated the use of three-dimensional (3D) anthropometric parameters derived from computed tomography (CT) scans and triglyceride glucose-body mass index (TyG-BMI) in relation to overall survival (OS) outcomes in advanced PDAC patients. Additionally, a predictive model for 1 year OS was developed based on body components and hematological indicators.
Methods: A retrospective analysis was conducted on 303 patients with locally advanced PDAC or synchronous metastases undergoing first-line chemotherapy, all of whom had undergone pretreatment abdomen-pelvis CT scans. Automatic 3D measurements of subcutaneous and visceral fat volume, skeletal muscle volume, and skeletal muscle density (SMD) were assessed at the L3 vertebral level by an artificial intelligence assisted diagnosis system (HY Medical). Various indicators including TyG-BMI, nutritional indicators [geriatric nutritional risk index (GNRI) and prealbumin], and inflammation indicators [(C-reactive protein (CRP) and neutrophil to lymphocyte ratio (NLR)] were also recorded. All patients underwent follow-up for at least 1 year and a dynamic nomogram for personalized survival prediction was constructed.
Results: We included 211 advanced PDAC patients [mean (standard deviation) age, 63.4 ± 11.2 years; 89 women (42.2) %)]. Factors such as low skeletal muscle index (SMI) (P = 0.011), high visceral to subcutaneous adipose tissue area ratio (VSR) (P < 0.001), high visceral fat index (VFI) (P < 0.001), low TyG-BMI (P = 0.004), and low prealbumin (P = 0.001) were identified as independent risk factors associated with 1 year OS. The area under the curve of the established dynamic nomogram was 0.846 and the calibration curve showed good consistency. High-risk patients (> 211.9 points calculated using the nomogram) had significantly reduced survival rates.
Conclusion: In this study, the proposed nomogram model (with web-based tool) enabled individualized prognostication of OS and could help to guide risk-adapted nutritional treatment for patients with unresectable PDAC or synchronous metastases.
期刊介绍：
No subject pertains more to human life than nutrition. The aim of Frontiers in Nutrition is to integrate major scientific disciplines in this vast field in order to address the most relevant and pertinent questions and developments. Our ambition is to create an integrated podium based on original research, clinical trials, and contemporary reviews to build a reputable knowledge forum in the domains of human health, dietary behaviors, agronomy & 21st century food science. Through the recognized open-access Frontiers platform we welcome manuscripts to our dedicated sections relating to different areas in the field of nutrition with a focus on human health.
Specialty sections in Frontiers in Nutrition include, for example, Clinical Nutrition, Nutrition & Sustainable Diets, Nutrition and Food Science Technology, Nutrition Methodology, Sport & Exercise Nutrition, Food Chemistry, and Nutritional Immunology. Based on the publication of rigorous scientific research, we thrive to achieve a visible impact on the global nutrition agenda addressing the grand challenges of our time, including obesity, malnutrition, hunger, food waste, sustainability and consumer health.
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