Xu Xin, Zhou Jin, Yao Xiaodong, Sang Shibiao, Li Jihui, Wang Bo, Yang Yi, Zhang Bin, Deng Shengming
Department of Nuclear Medicine, the First Affiliated Hospital of Soochow University, Suzhou, China.
Department of Nuclear Medicine, Shuyang Hospital Affiliated to Medical College of Yangzhou University, Suqian, China.
Quant Imaging Med Surg. 2024 Oct 1;14(10):7098-7110. doi: 10.21037/qims-24-852. Epub 2024 Sep 26.
Patients with lung cancer face a heightened risk of developing sarcopenia. Despite this known risk, the impact of sarcopenia on the long-term prognosis of lung cancer patients, specifically concerning progression-free survival (PFS) and overall survival (OS), remains unclear. The primary objective of our study was to examine the correlation between metabolic parameters derived from F-fluorodeoxyglucose positron emission tomography/computed tomography (F-FDG PET/CT) and sarcopenia, as well as the prognostic value of sarcopenia in patients with surgically resected early-stage non-small cell lung cancer (NSCLC).
In this retrospective cross-sectional study, we analyzed 187 NSCLC patients who underwent F-FDG PET/CT at the First Affiliated Hospital of Soochow University between March 2019 and October 2023. Patients were divided into two groups based on the presence (n=46) or absence (n=141) of sarcopenia. The correlation between sarcopenia, metabolic parameters, and patient characteristics was evaluated using chi-square and Mann-Whitney tests. Survival analyses, including PFS and OS, were conducted using Kaplan-Meier analysis and Cox proportional hazards regression. Based on sarcopenia, metabolic parameters and patient characteristics, patients were classified into high-risk (n=28), intermediate-risk (n=121), and low-risk (n=38) groups.
Our analysis identified gender, body mass index (BMI), psoas Hounsfield unit (HU), and maximum standardized uptake value of the psoas major muscle (SUV-Muscle) as independent predictors of sarcopenia (P<0.05 for all). A nomogram model, utilizing these parameters, was constructed to predict sarcopenia. Survival analysis further demonstrated that total lesion glycolysis [hazard ratio (HR) =2.499; 95% confidence interval (CI): 2.014-3.267; P=0.016], sarcopenia (HR =3.323; 95% CI: 1.748-6.316; P<0.001), and programmed death ligand-1 (PD-L1) expression (HR =0.093; 95% CI: 0.012-0.698; P=0.021) emerged as independent predictors of OS in early-stage NSCLC. Notably, patients categorized as high-risk, characterized by elevated total lesion glycolysis, presence of sarcopenia, and PD-L1 positivity, exhibited a significantly poorer prognosis compared to the intermediate-risk (P<0.05) and low-risk groups (P<0.05).
Our findings indicated an inverse relationship between SUV-Muscle or psoas HU with the incidence of sarcopenia in NSCLC patients. Additionally, total lesion glycolysis, sarcopenia, and PD-L1 expression were identified as independent prognostic factors for OS in early-stage NSCLC. The risk stratification model, incorporating total lesion glycolysis, sarcopenia, and PD-L1 expression, assumed a pivotal role in guiding personalized therapy decisions and post-treatment monitoring.
肺癌患者发生肌肉减少症的风险增加。尽管存在这种已知风险,但肌肉减少症对肺癌患者长期预后的影响,特别是关于无进展生存期(PFS)和总生存期(OS),仍不明确。我们研究的主要目的是探讨氟脱氧葡萄糖正电子发射断层扫描/计算机断层扫描(F-FDG PET/CT)得出的代谢参数与肌肉减少症之间的相关性,以及肌肉减少症在手术切除的早期非小细胞肺癌(NSCLC)患者中的预后价值。
在这项回顾性横断面研究中,我们分析了2019年3月至2023年10月期间在苏州大学附属第一医院接受F-FDG PET/CT检查的187例NSCLC患者。根据是否存在肌肉减少症将患者分为两组(存在肌肉减少症组,n = 46;不存在肌肉减少症组,n = 141)。使用卡方检验和曼-惠特尼检验评估肌肉减少症、代谢参数和患者特征之间的相关性。采用Kaplan-Meier分析和Cox比例风险回归进行生存分析,包括PFS和OS。根据肌肉减少症、代谢参数和患者特征,将患者分为高危组(n = 28)、中危组(n = 121)和低危组(n = 38)。
我们的分析确定性别、体重指数(BMI)、腰大肌Hounsfield单位(HU)和腰大肌最大标准化摄取值(SUV-Muscle)为肌肉减少症的独立预测因素(均P < 0.05)。利用这些参数构建了一个列线图模型来预测肌肉减少症。生存分析进一步表明,总病灶糖酵解[风险比(HR)= 2.499;95%置信区间(CI):2.014 - 3.267;P = 0.016]、肌肉减少症(HR = 3.323;95% CI:1.748 - 6.316;P < 0.001)和程序性死亡配体1(PD-L1)表达(HR = 0.093;95% CI:0.012 - 0.698;P = 0.021)是早期NSCLC患者OS的独立预测因素。值得注意的是,与中危组(P < 0.05)和低危组(P < 0.05)相比,以总病灶糖酵解升高、存在肌肉减少症和PD-L1阳性为特征的高危组患者预后明显较差。
我们的研究结果表明,SUV-Muscle或腰大肌HU与NSCLC患者肌肉减少症的发生率呈负相关。此外,总病灶糖酵解、肌肉减少症和PD-L1表达被确定为早期NSCLC患者OS的独立预后因素。纳入总病灶糖酵解、肌肉减少症和PD-L1表达的风险分层模型在指导个性化治疗决策和治疗后监测中发挥了关键作用。