Journal of Inflammation Research (Apr 2024)
A Nomogram Model Based on the Inflammation-Immunity-Nutrition Score (IINS) and Classic Clinical Indicators for Predicting Prognosis in Extranodal Natural Killer/T-Cell Lymphoma
Abstract
Yanxia He,1,* Zhumei Luo,1,* Haoqing Chen,2,3,* Liqing Ping,2,3 Cheng Huang,2,3 Yan Gao,2,3 Huiqiang Huang2,3 1Department of Oncology, The Third People’s Hospital of Chengdu, Sichuan, People’s Republic of China; 2State 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; 3Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Huiqiang Huang; Yan Gao, Department of Medical Oncology, Sun Yat-sen University Cancer Center, Guangzhou, People’s Republic of China, Email [email protected]; [email protected]: 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.Methods: 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.Results: 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.Conclusion: Compared with traditional prognostic systems, the nomogram showed promising prospects for risk stratification in ENKTL patient prognosis, providing new insights into the personalized treatment.Keywords: inflammation-immunity-nutrition score, extranodal natural killer/T-cell lymphoma, nomogram, prognosis, overall survival
