Suppr超能文献

慢性乙型肝炎病毒相关肝病中肝纤维化和炎症的非侵入性标志物

Noninvasive markers of liver fibrosis and inflammation in chronic hepatitis B-virus related liver disease.

作者信息

Mohamadnejad Mehdi, Montazeri Ghodrat, Fazlollahi Atoosa, Zamani Farhad, Nasiri Jafar, Nobakht Hossein, Forouzanfar Mohammad Hossein, Abedian Shifteh, Tavangar Seyed Mohamad, Mohamadkhani Ashraf, Ghoujeghi Farhad, Estakhri Arezoo, Nouri Negin, Farzadi Zahra, Najjari Abolfazl, Malekzadeh Reza

机构信息

Digestive Disease Research Center, Tehran University of Medical Sciences, Tehran, Iran.

出版信息

Am J Gastroenterol. 2006 Nov;101(11):2537-45. doi: 10.1111/j.1572-0241.2006.00788.x. Epub 2006 Oct 4.

Abstract

BACKGROUND/AIMS: Noninvasive markers for predicting significant fibrosis and inflammation have not yet been validated in an unselected group of chronic hepatitis B virus (HBV) carriers. The aim of this study was to create noninvasive models to predict significant fibrosis and inflammation in chronic HBV carriers.

METHODS

A total of 276 (229 HBeAg negative, 47 HBeAg positive) unselected consecutive treatment naïve patients chronically infected with HBV who attended our center over a 36-month period underwent liver biopsy. HBeAg negative patients were randomly divided into two cohorts: training group (N = 130) and validation group (N = 99). HBeAg positive patients were analyzed as a whole without separation. Thirteen parameters were analyzed separately in HBeAg negative and HBeAg positive patients to predict significant fibrosis (Ishak stage >or=3) and inflammation (Ishak grade >or=7).

RESULTS

In HBeAg negative patients significant liver fibrosis was best predicted using the variables HBV DNA levels, alkaline phosphatase, albumin, and platelet counts with an area under ROC curve (AUC) of 0.91 for the training group and 0.85 for the validation group. Using the low cutoff probability of 4.72, significant fibrosis could be excluded with negative predictive value of 99% in the entire cohort, and liver biopsy would have been avoided in 52% of patients. The best model for predicting significant inflammation included the variables age, HBV DNA levels, AST, and albumin with an AUC of 0.93 in the training and 0.82 in the validation group. In HBeAg positive patients no factor could predict accurately stages of liver fibrosis, but the best factor for predicting significant inflammation was AST with an AUC of 0.87.

CONCLUSIONS

Significant hepatic fibrosis and necroinflammation can reliably be predicted using routinely checked tests and HBV DNA levels.

摘要

背景/目的:用于预测显著纤维化和炎症的非侵入性标志物尚未在未选择的慢性乙型肝炎病毒(HBV)携带者群体中得到验证。本研究的目的是建立非侵入性模型来预测慢性HBV携带者的显著纤维化和炎症。

方法

在36个月期间,共有276例(229例HBeAg阴性,47例HBeAg阳性)未选择的、未经治疗的慢性HBV感染患者到我们中心接受肝活检。HBeAg阴性患者被随机分为两个队列:训练组(N = 130)和验证组(N = 99)。HBeAg阳性患者作为一个整体进行分析,不进行分组。分别对HBeAg阴性和HBeAg阳性患者的13个参数进行分析,以预测显著纤维化(Ishak分期≥3)和炎症(Ishak分级≥7)。

结果

在HBeAg阴性患者中,使用HBV DNA水平、碱性磷酸酶、白蛋白和血小板计数等变量可最佳预测显著肝纤维化,训练组的ROC曲线下面积(AUC)为0.91,验证组为0.85。使用4.72的低截断概率,在整个队列中可排除显著纤维化,阴性预测值为99%,52%的患者可避免肝活检。预测显著炎症的最佳模型包括年龄、HBV DNA水平、AST和白蛋白等变量,训练组的AUC为0.93,验证组为0.82。在HBeAg阳性患者中,没有因素能准确预测肝纤维化阶段,但预测显著炎症的最佳因素是AST,AUC为0.87。

结论

使用常规检查的指标和HBV DNA水平能够可靠地预测显著的肝纤维化和坏死性炎症。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验