肝硬化食管静脉曲张发生风险的超声内镜评估模型

A risk assessment model for esophageal varices occurrence based on endoscopic ultrasonography

目的以内镜超声检查术(EUS)为检测手段,明确肝硬化食管静脉曲张(EV)发生的独立危险因素,建立预测EV发生的危险评估模型,并对模型的临床预测价值进行评价。方法采用回顾性队列研究,以2014年9月至2017年3月于天津市第二人民医院住院治疗的无静脉曲张的肝硬化患者为研究对象,通过EUS测量并描述食管侧枝循环的位置、直径和数量,统计研究对象服用非选择性β受体阻滞剂(NSBB)及抗病毒治疗情况,以首次进行EUS检查时间为起点,随访期18个月,以EV发生或随访结束为终点。通过单因素及多因素logistic回归分析确定EV发生的独立危险因素,并构建起EV发生的危险评估模型。采用ROC曲线分析评价模型对疾病的预测价值。运用Hosmer-Lemeshow拟合优度检验评价模型的拟合效能。结果本研究最初招募研究对象638例,有13例于研究过程中失访,最终纳入研究625例,其中未发生EV者369例(未进展组)、发生EV者256例(进展组)。(1)多因素logistic回归分析提示7个独立危险因素最终入选EV发生危险评估模型并赋予相应分值:未服用NSBB(3分)、未接受抗病毒治疗(2分)、肝功能Child-pugh B级(1分)、食管周围侧枝静脉(peri-ECV)直径>2 mm(1分)、peri-ECV数量≥5条(3分)、食管旁侧枝静脉(para-ECV)直径≥5 mm(4分)、para-ECV数量≥5条(4分)。(2)危险评估模型中危险因素评分从1分到4分不等,总分为0~18分,EV的预测发生率随评分的升高呈上升趋势,预测发生率从0.003升至1.000。(3)危险评估模型中危险总评分≤2分为低危组,3~5分为中危组,≥6分为高危组,各个危险分层实际EV发生率分别为低危组2.78%、中危组36.36%、高危组93.91%。(4)采用ROC曲线对危险评估模型预测疾病进展的价值进行评估,结果显示ROC曲线下面积(AUC)=0.947(P<0.05),提示危险评估模型对疾病进展的预测效果很好。采用Hosmer-Lemeshow拟合优度检验对模型的拟合度进行检验,结果显示P=0.450,提示模型拟合情况较好。结论基于EUS构建起的危险评估模型能够较为准确地预测EV发生,且该模型具有简单、易用的特点,能够为肝硬化EV发生的预防及合理治疗策略的制定提供科学依据。

Objective To identify the independent risk factors of esophageal varices ( EV) in cirrhosis by endoscopic ultrasonography ( EUS) , and further to establish a risk assessment model for predicting EV occurrence and evaluate the clinical predictive value of the model. Methods A retrospective cohort study was used in this study. Data of patients with cirrhosis without varicosity, who were hospitalized in Tianjin Second People's Hospital from September 2014 to March 2017 were collected. The location, diameter, and number of esophageal collateral circulation were measured by EUS. The non-selective beta blocker ( NSBB) medication history and antiviral therapy were recorded. The time of the first EUS examination was taken as the starting point and the follow-up period was set up as 18 months. The end point was the occurrence of EV or the end of follow-up. The independent risk factors of EV occurrence were determined by univariate and multivariate logistic regression analysis, and the risk assessment model of EV occurrence was constructed. The predictive value of evaluation model for disease was studied by ROC analysis. Hosmer-Lemeshow goodness of fit was used to test the fitting efficiency of the evaluation model. Results A total of 638 subjects were recruited initially, 13 of them were lost in the course of the study. Finally, 625 cases were included in the study. Among them, 369 cases did not develop EV ( the non-progress group) and 256 cases developed EV (the progress group). (1) Multivariate logistic regression analysis showed that 7 independent risk factors were selected into the risk assessment model of EV occurrence, and were assigned corresponding scores:no NSBB (3 points), no antiviral treatment (2 points), Child-Pugh stage B (1 point), the diameter of peri-ECV>2 mm ( 1 point) , the number of peri-ECV≥5 ( 3 points) , the diameter of para-ECV≥5 mm ( 4 points) , and the number of para-ECV≥5 ( 4 points) . ( 2) In the risk assessment model, the risk factor scores ranged from 1 to 4 with a total score of 0-18. The predicted incidence of EV increased from 0. 003 to 1. 000 with the increase of the score. ( 3) In the risk assessment model, the total risk score≤2 was assigned into low-risk group, 3-5 into medium-risk group, and ≥6 into high-risk group. The actual EV incidence of each risk stratification was 2. 78% in the low-risk group, 36. 36% in the medium-risk group and 93. 91% in the high-risk group, respectively. (4) The ROC analysis showed that area under curve (AUC) was 0. 947 (P<0. 05), suggesting that the risk assessment model had a good effect on predicting disease progression. Hosmer-Lemeshow test showed that P was 0. 450, suggesting that the model fitted well. Conclusion The risk assessment model based on EUS can accurately predict the occurrence of EV, and is simple and easy to use. The model can provide scientific basis for the prevention and rational treatment of EV in liver cirrhosis.