本研究旨在更好地管理接受姑息性免疫化疗（PICT）的新发转移性鼻咽癌（NPC）患者，从而轻松确定个体生存结果。纳入来自四个中心且接受一线 PICT 的新发转移性鼻咽癌患者。我们在训练队列 (n = 296) 中使用逻辑回归模型开发了治疗前总生存 (OS) 预测的列线图。我们在验证队列中评估了该列线图的性能。总共包括 592 名患者。中位随访时间为 29.83 个月。骨转移（HR，2.46；95% CI，1.01-6.21；p = 0.049）和转移病灶数量> 3（HR，2.78；95% CI，1.24-6.24；p = 0.013）是独立的预后指标。产生了新的两类M1细分：M1a，定义为不存在共存骨转移且存在三个以上转移病灶； M1b，其特征是同时存在骨转移并且存在三个以上的转移病灶。 M1a 患者与 M1b 患者的 3 年 OS 率分别为 87.1% 和 60.3% (p < 0.001)。训练组和验证组的 C 指数分别为 0.652 和 0.581。训练队列中 1 年、2 年和 3 年曲线下面积 (AUC) 分别为 0.69、0.68、0.68，验证队列中分别为 0.64、0.6、0.6。 DCA 曲线还表明列线图具有良好的临床实用性。拟议的 M1 细分为接受 PICT 的患者提供了良好的 OS 隔离。版权所有 © 2024 Elsevier Ltd。保留所有权利。

This study aims to better manage de novo metastatic nasopharyngeal carcinoma (NPC) patients receiving palliative immuno-chemotherapy (PICT), thereby easily determining individual survival outcomes.Patients with de novo metastatic NPC from four centers who received first-line PICT were included. We developed a nomogram for the pretherapy overall survival (OS) prediction using a logistic regression model in the training cohort (n = 296). We assessed the performance of this nomogram in a validation cohort.A total of 592 patients were included. The median follow-up time was 29.83 months. Bone metastasis (HR, 2.46; 95 % CI, 1.01-6.21; p = 0.049) and the number of metastatic lesions > 3 (HR, 2.78; 95 % CI, 1.24-6.24; p = 0.013) were independent prognostic indicators. A new two-category M1 subdivision was generated: M1a, defined by the absence of co-existing bone metastasis and the presence of more than three metastatic lesions; and M1b, characterized by the presence of co-existing bone metastasis and the presence of more than three metastatic lesions. The 3-year OS rates of patients with M1a vs. M1b were 87.1 % vs. 60.3 % (p < 0.001). The C-indexes were 0.652 and 0.581 in the training and validation cohorts. The 1-, 2-, and 3-year areas under the curve (AUC) were 0.69, 0.68, 0.68 in the training cohort and 0.64, 0.6, 0.6 in the validation cohort. DCA curves also indicated that the nomogram has good clinical utility.The proposed M1 subdivision provides good OS segregation for patients receiving PICT.Copyright © 2024 Elsevier Ltd. All rights reserved.