摘要
目的 探究预后营养指数(PNI)、中性粒细胞与淋巴细胞比值(NLR)、血小板与淋巴细胞比值(PLR)对接受免疫检查点抑制剂(ICIs)治疗的晚期胃癌(AGC)疗效及预后价值评估.方法 回顾性分析新乡医学院第一附属医院2019年6月-2022年1月接受ICIs治疗75例AGC患者的临床资料.应用ROC曲线计算PNI、NLR、PLR最佳截断值.绘制Kaplan-Meier曲线并运用Cox比例风险模型预测影响AGC总生存期(OS)的独立危险因素.结果 PNI、NLR0、PLR0、PLR4的最佳截断值为36.00、3.45、186.65、138.23.高PNI组和低PLR0组客观缓解率(ORR)更高;高PNI组、低NLR0组、低PLR0组和低PLR4组疾病控制率(DCR)更高,差异均有统计学意义(P＜0.05).单因素分析显示,PNI、NLR0、PLR0、PLR4、BMI、分期均与OS相关.多因素分析显示,分期(HR=2.040,95％CI:1.120～3.730,P=0.020)及 PLR0(HR=3.539,95％CI:1.717～7.296,P＜0.001)是 OS 的独立影响因素.结论 PNI、NLR0、PLR0、PLR4对接受ICIs治疗的AGC疗效及预后具有临床指导价值.
Abstract
Objective To explore the efficacy and prognostic value of prognostic nutrition index(PNI),neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR)in advanced gastric cancer(AGC)treated with immune checkpoint inhibitors(ICIs).Methods A retrospective analysis was conducted on the clinical data of 75 AGC patients who received ICIs treatment at the First Affiliated Hospital of Xinxiang Medical College from June 2019 to January 2022.The ROC curve was used to calculate the optimal cutoff values for PNI,NLR,and PLR.Kaplan-Meier curves was plot-ted,and cox regression analysis was used to predict the independent risk factors affecting overall survival(OS)in AGC.Results The best cutoff values for PNI,NLRO,PLRO,and PLR4 were 36.00,3.45,186.65,and 138.23,respec-tively.The objective response rate(ORR)of high PNI group and low PLR0 group were higher.The disease control rate(DCR)of high PNI group,low NLR0 group,low PLR0 group and low PLR4 group were higher,and the differences were statistically significant(P＜0.05).Univariate analysis showed that PNI,NLR0,PLR0,PLR4,BMI and stage were cor-related with OS.Multivariate analysis showed that PLR0 was an independent risk factor for OS(HR=3.539,95％CI:1.717-7.296,P＜0.001)and PFS(HR=4.556,95％CI:1.955-10.617,P＜0.001)except stage.Conclusion Detection of PNI,NLRO,PLRO,and PLR4 has clinical guiding value for the efficacy and prognosis of AGC after ICIs treatment.
基金项目
国家自然科学基金项目(82302298)
河南省医学科技攻关计划联合共建项目(LHGJ20210523)
河南省医学科技攻关计划联合共建项目(LHGJ20220597)
河南省医学科技攻关计划项目(19A320003)
维普
万方数据