预测HBV相关肝细胞癌生存的列线图模型的建立

Establishment of a nomogram model for predicting the survival of hepatitis B virus-related hepatocellular carcinoma

目的筛选HBV相关肝细胞癌(HCC)死亡的危险因素并建立列线图预测模型。方法回顾性分析2010年1月—2020年1月在解放军总医院第五医学中心首次确诊为HBV相关HCC的700例患者的资料并进行随访,起点为HCC的诊断日期,终点为死亡。根据随访结果,分为死亡组(n=407)和生存组(n=293)。计量资料用组间比较采用独立样本t检验或Mann-Whitney U检验;计数资料组间比较采用χ^(2)检验;采用Kaplan-Meier法计算生存率,log-rank检验进行单因素分析,应用多变量Cox比例风险回归筛选独立危险因素,并构建可预测1、3、5年生存率的列线图模型,采用200次10折交叉验证法对模型进行评价。结果两组的性别构成、Alb、TBil、ALT、AFP、CHE、LSM及BCLC分期比较差异均有统计学意义(P值均<0.05)。多因素分析显示男性[风险比(HR)=1.390,95%CI:1.077~1.794]、CHE(2500~5000 U/L)(HR=1.996,95%CI:1.470~2.710)、CHE<2500 U/L(HR=3.210,95%CI:2.188~4.709)、AFP≥400 ng/mL(HR=1.803,95%CI:1.412~2.303)、肝弹性值≥17.5 kPa(HR=1.719,95%CI:1.349~2.190)、巴塞罗那分期B/C(HR=3.811,95%CI:2.994~4.852)、巴塞罗那分期D(HR=3.708,95%CI:2.520~5.455)为死亡的独立危险因素(P值均<0.05)。基于以上因素建立列线图模型,一致性指数为0.789(95%CI:0.769~0.809),校准曲线拟合良好,模型预测值与实际观测值之间的差异无统计学意义。结论本研究建立的列线图模型可以个体化预测HBV相关HCC患者的1、3、5年的生存率,有助于准确评估预后。

Objective To investigate the risk factors for death in hepatitis B virus(HBV)-related hepatocellular carcinoma(HCC),and to establish a nomogram predictive model.Methods A retrospective analysis was performed for the clinical data of 700 patients who were diagnosed with HBV-related HCC for the first time in The Fifth Medical Center of Chinese PLA General Hospital from January 2010 to January 2020,and the starting point of follow-up was the date of HCC diagnosis,with death as the endpoint.According to the results of follow-up,the patients were divided into death group with 407 patients and survival group with 293 patients.The independent samples t-test or the Mann-Whitney U test was used for comparison of continuous data between groups,and the chi-square test was used for comparison of categorical data between groups.The Kaplan-Meier method was used to calculate survival rates,and the log-rank test was used for univariate analysis.The multivariate Cox proportional-hazards regression model was used to screen out independent risk factors and establish a nomogram model to predict 1-,3-,and 5-year survival rates,and 10-fold cross validation was performed 200 times to evaluate the model.Results There were significant differences between the two groups in sex composition,albumin,total bilirubin,alanine aminotransferase,alpha-fetoprotein(AFP),cholinesterase(CHE),liver stiffness measurement(LSM),and Barcelona Clinic Liver Cancer(BCLC)stage(all P<0.05).The multivariate analysis showed that male sex(hazard ratio[HR]=1.390,95%confidence interval[CI]:1.077-1.794,P<0.05),CHE(2500-5000 U/L)(HR=1.996,95%CI:1.470-2.710,P<0.05),CHE<2500 U/L(HR=3.210,95%CI:2.188-4.709,P<0.05),AFP≥400 ng/mL(HR=1.803,95%CI:1.412-2.303,P<0.05),LSM≥17.5 kPa(HR=1.719,95%CI:1.349-2.190,P<0.05),BCLC stage B/C(HR=3.811,95%CI:2.994-4.852,P<0.05),and BCLC stage D(HR=3.708,95%CI:2.520-5.455,P<0.05)were independent risk factors for death.The nomogram model established based on the above factors had an index of concordance of 0.789(95%CI:0.769-0.809)with well-fitted calibration curves,and there was no significant difference between the predicted value of the model and the actual observed value.Conclusion The nomogram model established in this study can predict the 1-,3-,and 5-year survival rates of HBV-related HCC patients and help to accurately assess the prognosis of patients.