He Yanxia, Luo Zhumei, Chen Haoqing, Ping Liqing, Huang Cheng, Gao Yan, Huang Huiqiang
Department of Oncology, The Third People's Hospital of Chengdu, Sichuan, People's Republic of China.
State Key Laboratory of Oncology in South China, Collaborative Innovation Center of Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, People's Republic of China.
J Inflamm Res. 2024 Apr 4;17:2089-2102. doi: 10.2147/JIR.S452521. eCollection 2024.
Systemic inflammation, immunity, and nutritional status are closely related to patients' outcomes in several kinds of cancers. This study aimed to establish a new nomogram based on inflammation-immunity-nutrition score (IINS) to predict the prognosis of extranodal natural killer/T-cell lymphoma (ENKTL) patients.
The clinical data of 435 patients with ENTKL were retrospectively reviewed and randomly assigned to training cohort (n=305) and validation cohort (n=131) at a ratio of 7:3. Cox regression analysis was employed to identify independent prognostic factors and develop a nomogram in the training cohort. Harrell's concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) curve were employed to assess the performance of the nomogram and compare it with traditional prognostic systems (PINK, IPI, KPI). Internal validation was performed using 1000 bootstrap resamples in the validation cohort. Kaplan-Meier survival analyses were conducted to compare the overall survival (OS) of patients in different risk groups.
In the training cohort, in addition to several classic parameters, IINS was identified as an independent prognostic factor significantly associated with the OS of patients. The nomogram established based on the independent prognostic indicators showed superior survival prediction efficacy, with C-index of 0.733 in the training cohort and 0.759 in the validation cohort compared to the PINK (0.636 and 0.737), IPI (0.81 and 0.707), and KPI (0.693 and 0.639) systems. Furthermore, compared with PINK, IPI, and IPI systems, the nomogram showed relatively superior calibration curves and more powerful prognostic discrimination ability in predicting the OS of patients. DCA curves revealed some advantages in terms of clinical applicability of the nomogram compared to the PINK, IPI, and IPI systems.
Compared with traditional prognostic systems, the nomogram showed promising prospects for risk stratification in ENKTL patient prognosis, providing new insights into the personalized treatment.
全身炎症、免疫和营养状况与多种癌症患者的预后密切相关。本研究旨在基于炎症-免疫-营养评分（IINS）建立一种新的列线图，以预测结外自然杀伤/T细胞淋巴瘤（ENKTL）患者的预后。
回顾性分析435例ENTKL患者的临床资料，并按7:3的比例随机分为训练队列（n = 305）和验证队列（n = 131）。采用Cox回归分析确定独立预后因素，并在训练队列中建立列线图。采用Harrell一致性指数（C指数）、校准曲线、受试者工作特征（ROC）曲线和决策曲线分析（DCA）曲线评估列线图的性能，并与传统预后系统（PINK、IPI、KPI）进行比较。在验证队列中使用1000次自抽样重采样进行内部验证。进行Kaplan-Meier生存分析，以比较不同风险组患者的总生存期（OS）。
在训练队列中，除了几个经典参数外，IINS被确定为与患者OS显著相关的独立预后因素。基于独立预后指标建立的列线图显示出优越的生存预测效能，训练队列中的C指数为0.733，验证队列中的C指数为0.759，优于PINK（0.636和0.737）、IPI（0.81和0.707）和KPI（0.693和0.639）系统。此外，与PINK、IPI和IPI系统相比，列线图在预测患者OS方面显示出相对优越的校准曲线和更强的预后判别能力。DCA曲线显示，与PINK、IPI和IPI系统相比，列线图在临床适用性方面具有一些优势。
与传统预后系统相比，列线图在ENKTL患者预后风险分层方面显示出良好的前景，为个性化治疗提供了新的见解。
