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Multiparameter body composition analysis on chest CT predicts clinical outcomes in resectable non-small cell lung cancer

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机构: [1]Guangdong Acad Sci, Guangdong Prov Peoples Hosp, Guangdong Cardiovasc Inst, Guangzhou, Guangdong, Peoples R China [2]Southern Med Univ, Guangdong Prov Peoples Hosp, Guangdong Acad Med Sci, Dept Radiol, Guangzhou, Guangdong, Peoples R China [3]Guangdong Prov Key Lab Artificial Intelligence Med, Guangzhou, Guangdong, Peoples R China [4]Kunming Med Univ, Dept Med Imaging, Affiliated Hosp 1, Kunming, Yunnan, Peoples R China [5]Kunming Med Univ, Dept Intens Care Unit, Affiliated Hosp 1, Kunming, Yunnan, Peoples R China [6]South China Univ Technol, Guangzhou Peoples Hosp 1, Sch Med, Dept Radiol, Guangzhou, Guangdong, Peoples R China
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关键词: Lung cancer Body composition Disease-free survival Overall survival Computed tomography

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Objectives This study investigates the association between baseline CT body composition parameters and clinical outcomes in patients with resectable non-small cell lung cancer (NSCLC). Methods Patients who underwent surgical resection for NSCLC between January 2006 and December 2017 were retrospectively enrolled in this multicenter study. Body composition metrics, including the area of skeletal muscle, intermuscular adipose tissue, subcutaneous adipose tissue, visceral adipose tissue, muscle radiodensity, and derivative parameters from five basic metrics mentioned before, were calculated based on preoperative non-contrast-enhanced chest CT images at L1 level. The Cox proportional hazards regression analysis was used to evaluate the association between body composition metrics and survival outcomes including overall survival (OS) and disease-free survival (DFS). Results A total of 2712 patients (mean age, 61.53 years; 1146 females) were evaluated. A total of 635 patients (23.41%) died. 465 patients (19.51%) experienced recurrence and/or distant metastasis. After multivariable adjustment, skeletal muscle index (SMI, HR = 0.86), intermuscular adipose index (IMAI, HR = 1.49), and subcutaneous adipose index (SAI, HR = 0.96) were associated with OS. Similar results were found after stratification by gender, TNM stage, and center. There was no significant association between all body composition metrics and DFS (all p > 0.05). The body composition metrics significantly enhance the model including clinicopathological factors, resulting in an improved AUC for predicting 1-year and 3-year OS, with AUC values of 0.707 and 0.733, respectively. Conclusions SMI, IMAI, and SAI body composition metrics have been identified as independent prognostic factors and may indicate mortality risk for resectable NSCLC patients. Critical relevance statement Our findings emphasize the significance of muscle mass, quality, and fat energy storage in clinical decision-making for patients with non-small cell lung cancer (NSCLC). Nutritional and exercise interventions targeting muscle quality and energy storage could be considered for patients with NSCLC. Key Points <bold>.</bold>Multiparameter body composition analysis is associated with the clinical outcome in NSCLC patients. <bold>.</bold>Assessing muscle mass, quality, and adipose tissue helps predict overall survival in NSCLC. <bold>.</bold>The quantity and distribution of body composition can contribute to unraveling the adiposity paradox.

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大类 | 2 区 医学
小类 | 2 区 核医学
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Q1 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING

影响因子: 最新[2023版] 最新五年平均 出版当年[2024版] 出版当年五年平均 出版前一年[2023版]

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第一作者机构: [1]Guangdong Acad Sci, Guangdong Prov Peoples Hosp, Guangdong Cardiovasc Inst, Guangzhou, Guangdong, Peoples R China [2]Southern Med Univ, Guangdong Prov Peoples Hosp, Guangdong Acad Med Sci, Dept Radiol, Guangzhou, Guangdong, Peoples R China [3]Guangdong Prov Key Lab Artificial Intelligence Med, Guangzhou, Guangdong, Peoples R China [4]Kunming Med Univ, Dept Med Imaging, Affiliated Hosp 1, Kunming, Yunnan, Peoples R China
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通讯机构: [2]Southern Med Univ, Guangdong Prov Peoples Hosp, Guangdong Acad Med Sci, Dept Radiol, Guangzhou, Guangdong, Peoples R China [3]Guangdong Prov Key Lab Artificial Intelligence Med, Guangzhou, Guangdong, Peoples R China
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