中晚期原发性肝细胞癌ICIs相关不良反应风险预测模型的构建与验证  

Construction and verification of risk prediction model for ICIs-related adverse events of advanced primary hepatocellular carcinoma

作　　者：宋发祥 郭社民 王静 SONG Faxiang;GUO Shemin;WANG Jing(Drug Adverse Reaction Monitoring Center of Puyang City,Puyang,457000,Henan,China)

机构地区：[1]濮阳市药品不良反应监测中心,河南濮阳457000

出　　处：《肿瘤药学》2024年第6期747-752,共6页Anti-Tumor Pharmacy

基　　金：河南省卫生计生委科研课题(20221600)。

摘　　要：目的 探究中晚期原发性肝细胞癌(HCC)患者接受免疫检查点抑制剂(ICIs)治疗后相关不良反应(irAE)的发生情况,建立风险预测模型并验证。方法 回顾性分析2018年6月至2023年6月接受ICIs治疗的186例中晚期HCC患者的临床资料,根据患者是否发生irAE分为irAE组与对照组。采用单因素分析和多因素Logistic回归分析筛选发生irAE的独立影响因素,并构建风险预测模型。采用Bootstrap内部验证法和受试者工作特征(ROC)曲线及其曲线下面积进行验证。结果 共71例接受ICIs治疗的中晚期HCC患者发生irAE,对两组行单因素和Logistic回归多因素分析显示年龄、Child-Pugh评分、临床分期、预后营养指数(PNI)、免疫炎症指数(SII)及治疗方案是患者发生irAE的独立影响因素。据此构建的irAE风险预测列线图模型,平均绝对误差为0.02。ROC曲线分析显示,该模型的曲线下面积(AUC)为0.891(95%CI:0.845~0.937),最佳截断值为280,敏感度为83.10%,特异度为80.87%。结论 年龄、Child-Pugh评分、临床分期、PNI、SII及治疗方案是HCC患者接受ICIs治疗后发生irAE的独立影响因素,据此构建的列线图模型能有效预测中晚期HCC患者irAE的发生风险,具有较高的临床价值。Objective To explore the incidence of immune checkpoint inhibitors(ICIs)-related adverse events(irAEs)in patients with advanced hepatocellular carcinoma(HCC),and to develop and validate a risk prediction model.Methods A retrospective analysis was conducted on the clinical data of 186 HCC patients treated with ICIs between June 2018 and June 2023.The patients were divided into the irAE group and the control group based on whether they experienced an irAE.Logistic regression was employed to identify independent factors influencing the occurrence of irAEs in patients with advanced HCC and to construct a risk prediction model.Furthermore,the model was validated using the Bootstrap internal validation method and the area under the receiver operating characteristic curve(ROC).Results A total of 71 patients with advanced HCC who received ICIs developed irAEs.Univariate and multivariate Logistic regression analysis of the two groups revealed that age,Child-Pugh score,clinical stage,prognostic nutritional index(PNI),systemic immune inflamma-tion index(SII),and treatment regimen were independent factors influencing the occurrence of irAEs in patients.Based on these findings,a nomogram model for predicting the risk of irAEs was constructed,with a mean absolute error of 0.02.The performance of this model was evaluated using ROC,resulting in an area under the curve(AUC)of 0.891(95%CI:0.845-0.937).The optimal cut-off value was 280,with a sensitivity of 83.10%and a specificity of 80.87%.Conclusion Age,Child-Pugh score,clinical stage,PNI,SII,and treatment regimen were independent factors influencing the occurrence of irAEs in HCC patients after ICIs treatment.The nomogram model constructed based on these factors could effectively pre-dict the risk of irAEs in patients with advanced HCC,demonstrating significant clinical value.

关 键 词：肝细胞癌 免疫检查点抑制剂 免疫治疗相关不良反应 危险因素 列线图 预测模型 

分 类 号：R735.7[医药卫生—肿瘤] R969.3[医药卫生—临床医学]