首页|外周血炎症指标动态变化对晚期肝细胞癌免疫联合抗血管治疗疗效的预测价值:基于RESCUE临床试验随访数据的分析

外周血炎症指标动态变化对晚期肝细胞癌免疫联合抗血管治疗疗效的预测价值:基于RESCUE临床试验随访数据的分析

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背景 外周血炎症指标被认为是免疫治疗潜在的疗效预测标志物,但关于各指标的动态变化及联合预测效果的研究甚少.目的 探讨单独和联合应用外周血炎症指标动态变化对晚期肝细胞癌(hepatocellular carcinoma,HCC)免疫联合抗血管治疗疗效的预测价值.方法 选择接受卡瑞利珠单抗和甲磺酸阿帕替尼联合治疗的 189例晚期HCC患者.从基线开始至末次治疗后 30 d,每 2周检测 1次外周血,计算整个治疗过程中动态变化的外周血炎症指标,包括中性粒细胞与淋巴细胞比值(neutrophil to lymphocyte ratio,NLR)、血小板与淋巴细胞比值(platelet to lymphocyte ratio,PLR)、预后营养指数(prognostic nutritional index,PNI)和系统免疫炎症指数(systemic immune-inflammation index,SII).在时间依存性Cox回归模型中,治疗期间随时间变化的NLR、PLR、PNI和SII分别定义为时依NLR、PLR、PNI及SII,时依均值为各指标治疗期间的平均值.根据疗效,将 189例患者分为完全缓解(complete response,CR)/部分缓解(partial response,PR)组、病情稳定(stable disease,SD)组和疾病进展(progressive disease,PD)组,分析不同指标的基线值及时依均值与不同疗效的相关性.采用Kaplan-Meier法绘制生存曲线.采用单因素和多因素Cox比例风险回归模型及时间依存性Cox回归模型分析患者总生存期(overall survival,OS)的关联因素;应用一致性指数(C指数)评价各炎症指标单独及联合应用对OS的预测效能.结果 189例患者中,男 169例,女 20例,年龄≥60岁 44例.CR/PR组、SD组和PD组分别有 51例、95例和 38例,3组NLR[M(IQR):1.9(1.3~2.3)vs 2.2(1.6~3.2)vs 2.8(1.8~3.9),P<0.001]、PLR[M(IQR):87(67~104)vs 99(84~127)vs 131(86~179),P<0.001]和SII[M(IQR):233(166~266)vs 292(189~412)vs 376(233~695),P<0.001]时依均值的差异均有统计学意义.所有患者的中位OS为 21.7个月(95%CI:18.171~25.189).各炎症指标单独应用的多因素分析示,时依NLR、时依PLR、时依PNI和时依SII均是OS的独立关联因素(P<0.05).随着NLR、PLR和SII值的上升,OS风险比上升;随着PNI值的上升,OS风险比下降.在所有预测模型中,时依PLR、时依PNI和时依SII三项指标的联合预测效果最好,C指数为 0.750(95%CI:0.709~0.790).结论 外周血炎症指标预测晚期HCC免疫联合抗血管治疗中,低NLR、PLR、SII以及高PNI水平的患者疗效更好.与基线数据相比,整个观察期内的时依数据模型预测效果较好,其中时依PLR、时依PNI和时依SII三项指标的联合预测效果最好.
Dynamic changes of peripheral blood inflammatory markers for predicting effectiveness of immunotherapy combined with anti-angiogenesis therapy for advanced hepatocellular carcinoma:Analysis of RESCUE follow-up data
Background Peripheral blood inflammatory markers are considered to be indicators for predicting the effectiveness of immunotherapy.However,there are few studies on the dynamic changes and combined prediction effect of each marker.Objective To investigate the predictive value of single and combined application of dynamic changes in peripheral blood inflammatory markers for the effectiveness of immunotherapy combined with anti-angiogenesis therapy for advanced hepatocellular carcinoma(HCC).Methods This study included 189 patients with advanced HCC who received the combination therapy of camrelizumab and apatinib.From baseline to 30 days after the last treatment,peripheral blood was detected every 2 weeks,and the dynamic changes of peripheral blood inflammatory markers during the whole treatment were calculated,such as neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),prognostic nutritional index(PNI)and systemic immune-inflammation index(SII).In the time-dependent Cox regression model,the time-varying NLR,PLR,PNI and SII during treatment were defined as time-dependent NLR,PLR,PNI and SII,respectively,and the time-dependent mean was the mean value of each marker during treatment.The patients were divided into three groups based on efficacy,including complete response(CR)/partial response(PR)group,stable disease(SD)group,and progressive disease(PD)group.The correlation between the baseline values and the time-dependent mean values of each marker and the treatment effects was analyzed.The survival curve was drawn by Kaplan-Meier method.Univariate and multivariate Cox regression models,as well as time-dependent Cox regression models,were utilized to explore the related influencing factors of overall survival(OS).The concordance index(C-index)was used to evaluate the predictive efficacy of each inflammatory marker alone and in combination on OS.Results Among the 189 patients,there were 169 males and 20 females,and 44 patients were older than 60 years old.There were 51,95 and 38 patients in the CR/PR group,SD group,and PD group,respectively.The differences in time-dependent mean values of NLR(M[IQR]:1.9[1.3-2.3]vs 2.2[1.6-3.2]vs 2.8[1.8-3.9],P<0.001),PLR(M[IQR]:87[67-104]vs99[84-127]vs131[86-179],P<0.001)and SII(M[IQR]:233[166-266]vs292[189-412]vs 376[233-695],P<0.001)among the three groups were statistically significant.The median OS of all patients was 21.7 months(95%CI:18.171-25.189).Multivariate analysis of the individual application of the four markers showed that time-dependent NLR,time-dependent PLR,time-dependent PNI and time-dependent SII were independent related factors affecting OS(P<0.05).With an increase in the NLR,PLR and SII,the hazard ratio(HR)of OS increased.Conversely,as the PNI increased,the HR of OS decreased.Among all predictive models,the combined predictive of time-dependent PLR,time-dependent PNI and time-dependent SII demonstrated the best predictive effect,with a C-index of 0.750(95%CI:0.709-0.790).Conclusion The study of peripheral blood inflammatory markers in predicting the efficacy of immunotherapy combined with anti-angiogenesis therapy for advanced HCC shows that patients with lower levels of NLR,PLR,SII and higher levels of SII during treatment have better effectiveness.The predictive effect of the time-dependent model during the whole observation period is superior to the baseline data.Clearly,the combined prediction of the time-dependent PLR,time-dependent PNI and time-dependent SII exhibits the most accurate predictive effect.

hepatocellular carcinomaefficacysurvival analysisneutrophil to lymphocyte ratioplatelet to lymphocyte ratioprognostic nutritional indexsystemic immune-inflammation index

张婷、刘容锐、赵传华、徐建明

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解放军总医院第一医学中心肿瘤内科,北京 100853

解放军总医院第五医学中心肿瘤内科,北京 100853

肝肿瘤 疗效 生存分析 中性粒细胞与淋巴细胞比值 血小板与淋巴细胞比值 预后营养指数 系统免疫炎症指数

2024

解放军医学院学报
解放军总医院-军医进修学院

解放军医学院学报

CSTPCD
影响因子:0.811
ISSN:2095-5227
年,卷(期):2024.45(4)