摘要
目的通过分析启东市慢性乙型肝炎(CHB)临床队列患者肝癌发病的危险因素,构建预测CHB患者肝癌发病风险的列线图模型。方法选取2016年1月1日—12月31日于启东市第三人民医院肝病门诊就诊的年龄≥18周岁的CHB患者,均采用结构式问卷进行问卷调查。将肝癌发病作为主要研究结局,通过启东市癌症登记处获取队列研究结局。比较肝癌发病组与未发病组的基线临床特征。计量资料两组间比较采用成组t检验或Mann-Whitney U检验。计数资料组间比较采用χ^(2)检验或Fisher精确概率法。采用单因素Cox回归模型探索CHB患者肝癌发病风险的影响因素,计算风险比(HR)和95%可信区间(95%CI),将单因素Cox回归模型中有意义的变量纳入LASSO回归进行筛选,所得特征变量纳入多因素Cox回归以建立预测模型。采用列线图使复杂模型可视化,通过受试者工作特征曲线(ROC曲线)、一致性指数(C-index)和校准曲线评估列线图的预测效能,应用决策曲线评估列线图的临床实用性。结果共选取CHB患者1479例,排除已确诊为肝癌者58例,检验指标缺失者15例及基线问卷重要信息缺失者164例,最终纳入研究对象1242例。截至2023年12月31日,中位随访时间7.71年,共67例肝癌新发病例,肝癌发病密度为729.78/10万人年。肝癌组与非肝癌组患者比较,年龄、性别、受教育程度、肝硬化情况、肝硬化患病时间、糖尿病史、白蛋白、TBil、DBil、AST、ALT、GGT、ALP差异均有统计学意义(P值均<0.05)。多因素Cox回归分析显示,年龄增长(HR=1.07,95%CI:1.05~1.10,P<0.001)、较高的TBil水平(HR=1.98,95%CI:1.15~3.42,P=0.014)、较高的GGT水平(HR=2.41,95%CI:1.43~4.08,P=0.001)及较长的肝硬化患病时间(HR=1.09,95%CI:1.02~1.15,P=0.009)是CHB患者肝癌发病的独立危险因素,基于上述4项指标构建列线图,预测CHB患者在1、3、5年时肝癌发病风险的ROC曲线下面积分别为0.790、0.845和0.829,并
Objective To investigate the risk factors for liver cancer in patients with chronic hepatitis B(CHB)in the Qidong Chronic Hepatitis B cohort,and to construct a nomogram model for predicting the risk of liver cancer in CHB patients.Methods A structured questionnaire survey was conducted among the CHB patients,aged≥18 years,who attended the outpatient service of Qidong Third People’s Hospital from January 1 to December 31,2016.The onset of liver cancer was defined as the primary outcome,and the outcomes of the cohort were obtained from Qidong Cancer Registry.Baseline clinical features were compared;between the liver cancer group and the non-liver cancer group.The independent-samples t test or the Mann-Whitney U test was used for comparison of continuous data between two groups,and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups.The Cox regression model was used to analyze the risk factors for liver cancer in CHB patients and calculate their hazard ratio(HR)and 95%confidence interval(CI);the variables with statistical significance in the univariate Cox regression analysis were included in the LASSO regression analysis,and then the variables obtained were included in the multivariate Cox regression analysis to establish a predictive model.The nomogram was used to visualize the complex model.The receiver operating characteristic(ROC)curve,index of concordance(C-index),and the calibration curve were used to assess the predictive efficacy of the model,and the decision curve was used to evaluate the clinical practicability of the nomogram.Results A total of 1479 CHB patients were selected,among whom 58 patients with a confirmed diagnosis of liver cancer,15 with missing data on testing indicators,and 164 with missing data on important information in the questionnaire were excluded,and finally 1242 subjects were included in the study.Up to December 31,2023,there were 67 new cases of liver cancer after a median follow-up time of 7.71 years,and the incidence den
作者
朱逸晨
沙春霞
樊春笋
张铁军
ZHU Yichen;SHA Chunxia;FAN Chunsun;ZHANG Tiejun(Department of Epidemiology/Key Laboratory of Public Health Safety,Ministry of Education,School of Public Health,Fudan University,Shanghai 200032,China;Department of Infection Management,Qidong Third People’s Hospital,Qidong,Jiangsu 226200,China;Department of Scientific Research,Qidong People’s Hospital/Qidong Liver Cancer Institute/Affiliated Qidong Hospital of Nantong University,Qidong,Jiangsu 226200,China)
出处
《临床肝胆病杂志》
CAS
北大核心
2024年第12期2441-2449,共9页
Journal of Clinical Hepatology
基金
国家重点研发计划(2021YFC2500405)。
关键词
乙型肝炎
慢性
肝肿瘤
危险因素
列线图
Hepatitis B,Chronic
Liver Neoplasms
Risk Factors
Nomograms
