程序性死亡受体1抑制剂治疗乙型肝炎相关肝癌预后列线图模型的构建与验证

Construction and validation of a prognostic nomogram model of programmed death receptor 1 inhibitors in treatment of hepatitis B-related hepatocellular carcinoma

目的探讨程序性死亡受体1(PD-1)抑制剂治疗乙型肝炎(简称:乙肝)相关肝癌预后的影响因素,建立该类患者预后列线图模型并评价其临床意义。方法回顾性分析2018年7月至2021年7月于新乡医学院第一附属医院经PD-1抑制剂治疗的121例乙肝相关肝癌患者的临床资料。从使用PD-1抑制剂开始进行随访,采用Kaplan-Meier法分析患者总生存。将单因素Cox比例风险模型分析筛选出的变量及临床中认为与预后有关的变量纳入总生存的多因素Cox比例风险模型,采用逐步回归法筛选总生存的独立影响因素。根据总生存独立影响因素,运用R3.5.1软件建立PD-1抑制剂治疗乙肝相关肝癌的总生存列线图模型。采用校准曲线评估模型预测与实际的一致性,采用Harrell一致性指数和受试者工作特征(ROC)曲线(以影像学诊断为金标准)分析模型预测患者1、2年总生存率的效果。结果121例患者中位随访12.40个月,中位总生存时间为14.30个月,6、12个月总生存率分别为82.60%、62.30%。多因素Cox回归分析显示,清蛋白(ALB)(HR=0.946,95%CI 0.901~0.992)、国际标准化比值(INR)(HR=32.034,95%CI 5.046~203.362)、天冬氨酸氨基转移酶(AST)(HR=1.010,95%CI 1.007~1.012)是患者总生存的独立影响因素,根据这3个因素建立了PD-1抑制剂治疗乙肝相关肝癌的预后列线图模型。模型预测1、2年总生存率的校准曲线斜率均接近于1。列线图模型的Harrell一致性指数为0.809(95%CI 0.760~0.858)。ROC曲线分析示,列线图模型预测患者1年和2年总生存率的曲线下面积(AUC)分别为0.794(95%CI 0.744~0.887,P<0.001)和0.791(95%CI 0.708~0.860,P=0.002)。结论ALB、INR、AST是PD-1抑制剂治疗乙肝相关肝癌患者预后的影响因素。基于预后影响因素构建的列线图模型有较好的预测患者1、2年总生存率的效果,可用于筛选适合免疫治疗的人群,有利于临床制定个体化精准治疗方案。

Objective To investigate the factors influencing the prognosis of hepatitis B-related hepatocellular carcinoma treated with programmed death receptor 1(PD-1)inhibitors,and to construct a prognostic nomogram model for these patients and evaluate its clinical significances.Methods The clinical data of 121 patients with hepatitis B-related hepatocellular carcinoma treated with PD-1 inhibitors at the First Affiliated Hospital of Xinxiang Medical College from July 2018 to July 2021 were retrospectively analyzed.Follow-up was performed from the beginning of PD-1 inhibitor use,and the Kaplan-Meier method was used to analyze the overall survival of patients.The variables screened by the univariate Cox proportional hazards model analysis and variables clinically believed to be related to the prognosis were included in the multivariate Cox proportional hazards model for overall survival,and the stepwise regression method was used to screen the independent factors influencing overall survival.Based on the independent influencing factors of overall survival,R 3.5.1 software was used to construct a prognostic nomogram model for overall survival of hepatitis B-related hepatocellular carcinoma treated with PD-1 inhibitors.Calibration curve was used to the consistency of model prediction and practice.The Harrell consistency index and receiver operating characteristic(ROC)curve(with imaging diagnosis as the gold standard)were used to analyze the efficacy of model in predicting the 1-year and 2-year overall survival rates.Results The median follow-up time of 121 patients was 12.40 months,and the median overall survival time was 14.30 months,with overall survival rates of 82.60%and 62.30%at 6 and 12 months.Multivariate Cox regression analysis showed that albumin(ALB)(HR=0.946,95%CI 0.901-0.992),international normalized ratio(INR)(HR=32.034,95%CI 5.046-203.362),aspartate aminotransferase(AST)(HR=1.010,95%CI 1.007-1.012)were independent influencing factors for overall survival of patients.According to the three factors,a prognostic nomogram model for hepatitis B-related hepatocellular carcinoma treated with PD-1 inhibitors was constructed.The slope of the calibration curve of the model predicting 1-year and 2-year overall survival rates was close to 1.The Harrell consistency index of the nomogram model was 0.809(95%CI 0.760-0.858).ROC curve analysis showed that the area under the curve(AUC)of the nomogram model predicting 1-year and 2-year overall survival rates of patients was 0.794(95%CI 0.744-0.887,P<0.001)and 0.791(95%CI 0.708-0.860,P=0.002).Conclusions ALB,INR and AST are the influencing factors of prognosis of hepatitis B-related hepatocellular carcinoma patients treated with PD-1 inhibitors,and the nomogram model constructed based on prognostic influencing factors has a good effect on predicting the 1-year and 2-year overall survival rates of patients,which can be used to screen the population suitable for immunotherapy and is conducive to the clinical formulation of individualized and precise treatment plans.