Prognostic value of inflammation-based prognostic index in patients with nasopharyngeal carcinoma: a propensity score matching study. 2018

Ronald Wihal Oei, and Lulu Ye, and Fangfang Kong, and Chengrun Du, and Ruiping Zhai, and Tingting Xu, and Chunying Shen, and Xiaoshen Wang, and Xiayun He, and Lin Kong, and Chaosu Hu, and Hongmei Ying
Department of Radiation Oncology, Fudan University Shanghai Cancer Center, Shanghai, People's Republic of China, dryinghongmei@163.com.

OBJECTIVE The aim of this article is to investigate the significance of pretreatment prognostic nutritional index (PNI), systemic immune-inflammation index (SII), and their combination in nasopharyngeal carcinoma (NPC) patients receiving intensity-modulated radiotherapy (IMRT). METHODS A total of 585 patients were included. PNI and SII were calculated within 2 weeks prior to treatment. The optimal cutoff points were determined based on receiver operating characteristics curve analysis. The correlation between variables was analyzed. Kaplan-Meier method and Cox proportional hazards model were performed to evaluate the impact of both indices on overall survival (OS), progression-free survival (PFS) and distant metastasis-free survival (DMFS). Further propensity score matching (PSM) was carried out to minimize the effects of confounders. RESULTS The optimal cutoff point of 53.0 for PNI and 527.20 for SII were selected. Pearson correlation coefficient showed an inverse correlation between PNI and SII (r = -0.232, P < 0.001). Multivariate analysis demonstrated that pretreatment PNI was an independent prognostic factor for OS (P = 0.047) and DMFS (P = 0.002) while pretreatment SII was an independent prognostic factor for OS (P = 0.003), PFS (P = 0.002), and DMFS (P = 0.002). After PSM, both parameters remained as independent prognosticators of survival. Additional prognostic value was observed in the combined use of PNI and SII. CONCLUSIONS Pretreatment PNI and SII are promising indicators of survival in NPC patients undergoing IMRT. They can be utilized to refine current TNM staging system in predicting prognosis and developing an individualized treatment in these patients.

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