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The prognostic value of the ratio of neutrophils to lymphocytes before and after intensity modulated radiotherapy for patients with nasopharyngeal carcinoma

机译：鼻咽癌患者强度调制放疗前后中性粒细胞与淋巴细胞比例的预后值

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This study aimed to determine the impact of the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) on the prognosis of nasopharyngeal carcinoma (NPC) before and after intensity modulated radiotherapy (IMRT). Pre/post-treatment and changes in inflammatory biomarker levels of 207 patients who were diagnosed with NPC and received IMRT between January 2012 and December 2014 were analyzed, and the cellular biomarker analyses were from patient blood. ROC (receiver operating characteristic) analysis was used to decide the optimal cutoff values of NLR and changes in NLR (ΔNLR) and PLR (ΔPLR). The Kaplan–Meier and logarithmic rank methods were used to compare overall survival times between groups. Univariate analysis was used to investigate the effects of age, gender, histology, Karnofsky performance score (KPS), TNM stage, clinical stage, course of disease and lymphocyte, neutrophil and platelet counts as well as alkaline phosphatase (ALP) levels on the prognosis of NPC. The independent predictors of OS were determined by Cox multivariate regression analysis. The optimal cut-off values of NLR, PLR, ΔNLR and ΔPLR were 2.49, 155.82, 1.80, and 100.00, respectively. These were used to classify patients into high (NLR 2.49) and low NLR groups (NLR 155.82) and low (PLR 1.80) and low ΔNLR groups (ΔNLR 100.00) and low ΔPLR groups (ΔPLR 100.00). TNM stage, clinical stage and ALP levels were highly correlated with high NLR and PLR. Cox multivariate regression analysis suggested that the ΔNLR (HR = 2.89, 95% CI: 1.33～2.78) was independent of the characteristics for NPC. As a novel inflammatory index, ΔNLR appears to have some predictive power for the prognosis of patients with NPC.
机译：本研究旨在确定中性粒细胞对淋巴细胞比（NLR）和血小板到淋巴细胞比（PLR）对强度调节放疗前后鼻咽癌（NPC）预后的影响（IMRT）。分析了预/后治疗和炎症生物标志物的变化，炎症生物标志物在2012年1月至2014年1月至2014年1月期间接受了IMRT，并且细胞生物标志物分析来自患者血液。 ROC（接收器操作特征）分析用于确定NLR的最佳截止值和NLR（ΔnLR）和PLR（ΔPLR）的变化。 KAPLAN-MEIER和对数等级方法用于比较组之间的整体生存时间。使用单变量分析来研究年龄，性别，组织学，Karnofsky性能评分（KPS），TNM阶段，临床阶段，疾病和淋巴细胞，中性粒细胞和血小板计数以及预后的碱性磷酸酶（ALP）水平的影响NPC。通过Cox多变量回归分析确定OS的独立预测因子。 NLR，PLR，ΔnLR和ΔPLR的最佳截止值分别为2.49,155.82,1.80和100.00。这些用于将患者分类为高（NLR> 2.49）和低NLR基团（NLR 155.82）和低（PLR 1.80）和低ΔnLR组（ΔnLR100.00）和低ΔPLR组（ΔPLR<100.00）。 TNM阶段，临床阶段和ALP水平与高NLR和PLR高度相关。 Cox多变量回归分析表明，Δnlr（hr = 2.89,95％ci：1.33〜2.78）与NPC的特征无关。作为一种新型炎症指数，Δnlr似乎对NPC患者的预测具有一些预测力。

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