Liu Daojia, Lin Duanyu, Lin Zhongmei, Peng Ying, Cai Siqian, Yang Qiwei, Lin Zhizhong, Chen Yuanmei, Shen Yongshi, Xu Yuanji
Department of Nuclear Medicine, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
Department of Radiation Oncology, Clinical Oncology School of Fujian Medical University, Fujian Cancer Hospital, Fuzhou, China.
J Thorac Dis. 2024 Nov 30;16(11):7853-7865. doi: 10.21037/jtd-24-1698. Epub 2024 Nov 29.
There is currently no widely accepted prognostic model specifically for elderly patients with esophageal squamous cell carcinoma (ESCC) undergoing radiotherapy. This study aimed to develop a nomogram incorporating metabolic imaging parameters from F-fluorodeoxyglucose positron emission tomography-computed tomography (F-FDG PET/CT) to predict overall survival (OS) in this patient population. The clinical need for such a prediction model is significant given the challenges of treatment planning in elderly patients with ESCC undergoing radiotherapy.
A retrospective analysis was conducted on 118 elderly patients with ESCC treated with radiotherapy. The patients were evaluated using F-FDG PET/CT imaging prior to treatment, and the spleen:liver ratio (SLR) and length of visual tumor (Lv) were identified as potential prognostic indicators. These variables, along with clinical tumor, node, metastasis (cTNM) staging, were used to develop a nomogram model. Key baseline clinical factors, PET variables, inclusion criteria, and follow-up procedures were documented. The model's predictive accuracy was assessed using time-dependent receiver operating characteristic (ROC) curves, the concordance index (C-index), and decision curve analysis (DCA). The patient cohort was stratified into three risk groups based on the total scores derived from the nomogram.
SLR and Lv were found to be independent predictors of OS in elderly patients with ESCC. The nomogram developed by incorporating these factors, along with cTNM staging, showed superior predictive power compared to the traditional TNM staging system. ROC curve analysis demonstrated greater accuracy in predicting 1-, 2-, and 3-year OS rates, with area under the curve (AUC) values of 0.771, 0.763, and 0.815, respectively. DCA confirmed that the nomogram provided a greater clinical benefit. Patients were stratified into low-risk, intermediate-risk, and high-risk groups, with corresponding 3-year OS rates of 60.3%, 25.0%, and 3.6%, respectively.
The developed nomogram incorporating SLR, Lv, and cTNM staging offers a reliable tool for the risk stratification of elderly patients with ESCC undergoing radiotherapy. This model may serve as a reference for personalized treatment planning, potentially improving clinical outcomes in this patient population.
目前尚无专门针对接受放疗的老年食管鳞状细胞癌（ESCC）患者被广泛接受的预后模型。本研究旨在开发一种列线图，纳入来自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）的代谢成像参数，以预测该患者群体的总生存期（OS）。鉴于接受放疗的老年ESCC患者治疗计划面临的挑战，对这种预测模型的临床需求十分显著。
对118例接受放疗的老年ESCC患者进行回顾性分析。在治疗前使用F-FDG PET/CT成像对患者进行评估，确定脾肝比（SLR）和肿瘤可视长度（Lv）为潜在的预后指标。这些变量与临床肿瘤、淋巴结、转移（cTNM）分期一起用于开发列线图模型。记录关键的基线临床因素、PET变量、纳入标准和随访程序。使用时间依赖受试者工作特征（ROC）曲线、一致性指数（C指数）和决策曲线分析（DCA）评估模型的预测准确性。根据列线图得出的总分将患者队列分为三个风险组。
发现SLR和Lv是老年ESCC患者OS的独立预测因素。纳入这些因素以及cTNM分期开发的列线图显示出比传统TNM分期系统更强的预测能力。ROC曲线分析表明，在预测1年、2年和3年OS率方面具有更高的准确性，曲线下面积（AUC）值分别为0.771、0.763和0.815。DCA证实列线图提供了更大的临床益处。患者被分为低风险、中风险和高风险组，相应的3年OS率分别为60.3%、25.0%和3.6%。
所开发的纳入SLR、Lv和cTNM分期的列线图为接受放疗的老年ESCC患者的风险分层提供了可靠工具。该模型可为个性化治疗计划提供参考，有可能改善该患者群体的临床结局。
