文章摘要
陈莉莉,李 鑫,康晓慧,秦 玥,魏文艳.术前预后营养指数、中性粒细胞与淋巴细胞比值及血小板与淋巴细胞比值对脑胶质瘤患者术后预后的评估价值研究[J].,2023,(5):845-849
术前预后营养指数、中性粒细胞与淋巴细胞比值及血小板与淋巴细胞比值对脑胶质瘤患者术后预后的评估价值研究
Evaluation Value Study of Preoperative Prognostic Nutritional Index, Neutrophil to Lymphocyte Ratio and Platelet to Lymphocyte Ratio on Postoperative Prognosis of Patients with Brain Glioma
投稿时间:2022-06-24  修订日期:2022-07-20
DOI:10.13241/j.cnki.pmb.2023.05.009
中文关键词: 脑胶质瘤  预后营养指数  中性粒细胞与淋巴细胞比值  血小板与淋巴细胞比值  预后
英文关键词: Brain glioma  Prognostic nutritional index  Neutrophil to lymphocyte ratio  Platelet to lymphocyte ratio  Prognosis
基金项目:首都医科大学附属北京天坛医院青年科研基金项目(2021-YQN-09);北京市自然科学基金资助项目(7182049)
作者单位E-mail
陈莉莉 首都医科大学附属北京天坛医院国际部 北京 100070 chenlili2211@163.com 
李 鑫 首都医科大学附属北京天坛医院国际部 北京 100070  
康晓慧 首都医科大学附属北京天坛医院国际部 北京 100070  
秦 玥 首都医科大学附属北京天坛医院国际部 北京 100070  
魏文艳 首都医科大学附属北京天坛医院国际部 北京 100070  
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中文摘要:
      摘要 目的:探讨术前预后营养指数(PNI)、中性粒细胞与淋巴细胞比值(NLR)及血小板与淋巴细胞比值(PLR)对脑胶质瘤患者术后预后的评估价值。方法:回顾性分析2016年2月至2019年2月我院收治的131例脑胶质瘤患者(脑胶质瘤组)的临床资料,另选择同期86例于门诊健康体检的志愿者为对照组,收集相关资料计算PNI、NLR、PLR。比较脑胶质瘤患者不同临床病理特征PNI、NLR、PLR的差异,Kaplan-Meier法绘制不同PNI、NLR、PLR水平脑胶质瘤患者的生存曲线,单因素和多因素COX回归分析影响脑胶质瘤患者预后的相关因素,受试者工作特征曲线(ROC)分析术前PNI、NLR、PLR预测脑胶质瘤患者预后的价值。结果:脑胶质瘤组NLR、PLR高于对照组(P<0.05),PNI低于对照组(P<0.05)。世界卫生组织(WHO)分级Ⅲ 级患者NLR、PLR高于WHO分级Ⅰ~Ⅱ级患者(P<0.05),PNI低于WHO分级Ⅰ~Ⅱ级患者(P<0.05)。高NLR组、高PLR组3年生存率低于低NLR组、低PLR组(P<0.05),低PNI组3年生存率低于高PNI组(P<0.05)。WHOⅢ级、NLR(较高)、PLR(较高)是脑胶质瘤患者预后不良的危险因素(P<0.05),PNI(较高)是保护因素(P<0.05)。术前PNI、NLR、PLR联合预测脑胶质瘤患者预后的曲线下面积为0.849,高于单独指标预测的0.703、0.706、0.704。结论:脑胶质瘤患者术前PNI降低,NLR、PLR均升高,且与预后不良有关,术前PNI、NLR、PLR可作为脑胶质瘤患者预后评估的参考指标。
英文摘要:
      ABSTRACT Objective: To investigate the value of preoperative prognostic nutritional index (PNI), neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) in the evaluation of postoperative prognosis in patients with brain glioma. Methods: The clinical data of 131 patients with brain glioma (brain glioma group) who were admitted to our hospital from February 2016 to February 2019 were retrospectively analyzed, and 86 healthy volunteers who underwent physical examination in the outpatient department during the same period were selected as the control group. The relevant data were collected and PNI, NLR and PLR were calculated. The differences of PNI, NLR and PLR in patients with brain glioma with different clinicopathological characteristics were compared. Kaplan-Meier method was used to draw the survival curves of patients with brain glioma with different levels of PNI, NLR and PLR. Univariate and multivariate COX regression analysis was used to analyze the related factors affecting the prognosis of patients with brain glioma. Receiver operating characteristic curve (ROC) was used to analyze the value of preoperative PNI, NLR and PLR in predicting the prognosis of patients with brain glioma. Results: The NLR and PLR in the brain glioma group were higher than those in the control group (P<0.05), and PNI was lower than that in the control group (P<0.05). The NLR and PLR of patients with World Health Organization (WHO) grade Ⅲ were higher than those of patients with WHO grade Ⅰ~Ⅱ (P<0.05), and the PNI was lower than that of patients with WHO grade Ⅰ~Ⅱ (P<0.05). The 3-year survival rate of high NLR group and high PLR group were lower than those of low NLR group and low PLR group (P<0.05), and the 3-year survival rate of low PNI group was lower than that of high PNI group (P<0.05). WHO grade Ⅲ, NLR (higher) and PLR (higher) were risk factors for poor prognosis in patients with brain glioma (P<0.05), and PNI (higher) was a protective factor (P<0.05). The area under curve of preoperative PNI, NLR and PLR combined to predict the prognosis of patients with brain glioma was 0.849, which was higher than the prediction of 0.703, 0.706 and 0.704 by single indicator. Conclusion: Preoperative PNI is decreased, NLR and PLR are increased in patients with brain glioma, which are related to poor prognosis. Preoperative PNI, NLR and PLR can be used as reference indicators for prognosis assessment of patients with brain glioma.
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