Zhang Jiayan, Yu Jiayi, Zhang Dan, Liu Qian, Li Qian, Song Zuhua, Zhou Bi, Tang Zhuoyue
Department of Radiology, Chongqing General Hospital, Chongqing, China.
Department of Radiology, Affiliated Hospital of Southwest Medical University, Luzhou, China.
Clin Otolaryngol. 2025 Nov;50(6):1026-1034. doi: 10.1111/coa.70011. Epub 2025 Jul 17.
This retrospective study aimed to establish a convenient and effective online dynamic nomogram for predicting progression-free survival (PFS) in nasopharyngeal carcinoma (NPC).
The clinical and imaging characteristics were retrospectively collected from 106 patients with pathologically confirmed NPC. Univariate and multivariate Cox proportional hazards regression analyses were performed to select the independent prognostic factors and construct a nomogram for predicting 1-, 3-, and 5-year PFS. The predictive effectiveness and clinical utility of the nomogram were evaluated by concordance index (C-index), calibration curves, and decision curve analysis (DCA). Patients were divided into different groups by risk score based on the nomogram, and the PFS rates of these two groups were compared by Kaplan-Meier curves.
Univariate and multivariate analyses indicated that the ADC (OR 0.177, 95% CI 0.068-0.464), extranodal neoplastic spread (ENS) (OR 3.662, 95% CI 1.495-8.968), and lymphocyte-to-monocyte ratio (LMR) (OR 2.688, 95% CI 1.094-6.607) at baseline were independent prognostic factors of NPC, with all p < 0.05. The nomogram revealed favourable predictive performance (C-index = 0.795). The area under the receiver operating characteristic curve (AUC) of the nomogram for predicting 1-, 3-year, and 5-year PFS was 0.792, 0.849, and 0.822, respectively, which outperformed the AJCC 8th TNM staging system (AUC = 0.592, 0.543, and 0.575). Besides, the nomogram distinguished the PFS rates well between low-and high-risk groups (p < 0.0001).
The online dynamic nomogram based on ADC, ENS, and LMR can divide NPC patients into different risk groups, and its prediction efficiency is better than the TNM stage system.
本回顾性研究旨在建立一种方便有效的在线动态列线图，用于预测鼻咽癌（NPC）的无进展生存期（PFS）。
回顾性收集106例经病理确诊的NPC患者的临床和影像特征。进行单因素和多因素Cox比例风险回归分析，以选择独立预后因素并构建预测1年、3年和5年PFS的列线图。通过一致性指数（C指数）、校准曲线和决策曲线分析（DCA）评估列线图的预测有效性和临床实用性。根据列线图的风险评分将患者分为不同组，通过Kaplan-Meier曲线比较这两组的PFS率。
单因素和多因素分析表明，基线时的表观扩散系数（ADC）（OR 0.177，95%CI 0.068-0.464）、结外肿瘤扩散（ENS）（OR 3.662，95%CI 1.495-8.968）和淋巴细胞与单核细胞比值（LMR）（OR 2.688，95%CI 1.094-6.607）是NPC的独立预后因素，所有p<0.05。列线图显示出良好的预测性能（C指数=0.795）。预测1年、3年和5年PFS的列线图的受试者操作特征曲线（AUC）下面积分别为0.792、0.849和0.822，优于美国癌症联合委员会（AJCC）第8版TNM分期系统（AUC=0.592、0.543和0.575）。此外，列线图能很好地区分低风险和高风险组的PFS率（p<0.0001）。
基于ADC、ENS和LMR的在线动态列线图可将NPC患者分为不同风险组，其预测效率优于TNM分期系统。
