慢性HBV感染患者HBsAg血清清除率预测模型

StephenW

Prediction Model of HBsAg Seroclearance in Patients with Chronic HBV Infection
Jing Cao  1 , Jiao Gong  2 , Christ-Jonathan Tsia Hin Fong  3 , Cuicui Xiao  4 , Guoli Lin  1 , Xiangyong Li  1 , Yusheng Jie  1 , Yutian Chong  1
Affiliations
Affiliations

    1
    Department of Infectious Diseases, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630 Guangdong Province, China.
    2
    Department of Laboratory Medicine, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630 Guangdong Province, China.
    3
    Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630 Guangdong Province, China.
    4
    Department of Anesthesiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510630 Guangdong Province, China.

    PMID: 32855968 PMCID: PMC7443222 DOI: 10.1155/2020/6820179

Free PMC article
Abstract

Background: Prediction of HBsAg seroclearance, defined as the loss of circulating HBsAg with or without development of antibodies for HBsAg in patients with chronic hepatitis B (CHB), is highly difficult and challenging due to its low incidence. This study is aimed at developing and validating a nomogram for prediction of HBsAg loss in CHB patients.

Methods: We analyzed a total of 1398 patients with CHB. Two-thirds of the patients were randomly assigned to the training set (n = 918), and one-third were assigned to the validation set (n = 480). Univariate and multivariate analysis by Cox regression analysis was performed using the training set, and the nomogram was constructed. Discrimination and calibration were performed using the training set and validation set.

Results: On multivariate analysis of the training set, independent factors for HBsAg loss including BMI, HBeAg status, HBsAg titer (quantitative HBsAg), and baseline hepatitis B virus (HBV) DNA level were incorporated into the nomogram. The HBsAg seroclearance calibration curve showed an optimal agreement between predictions by the nomogram and actual observation. The concordance index (C-index) of nomogram was 0.913, with confirmation in the validation set where the C-index was 0.886.

Conclusions: We established and validated a novel nomogram that can individually predict HBsAg seroclearance and non-seroclearance for CHB patients, which is clinically unprecedented. This practical prognostic model may help clinicians in decision-making and design of clinical studies.

Copyright © 2020 Jing Cao et al.
Conflict of interest statement

No conflicts of interest were declared for all authors.

StephenW

慢性HBV感染患者HBsAg血清清除率预测模型
曹操1，焦功2，克里斯蒂安乔纳森·蔡显芳3，翠翠小4，林国立1，李向勇1，俞胜杰1，俞天冲1
隶属关系
隶属关系

    1个
    中山大学附属第三医院感染科，广东广州510630
    2
    中山大学附属第三医院检验医学科，广东广州510630
    3
    中山大学附属第三医院消化内科，广东广州510630
    4
    中山大学附属第三医院麻醉科，广东广州510630

    PMID：32855968 PMCID：PMC7443222 DOI：10.1155 / 2020/6820179

免费PMC文章
抽象

背景：HBsAg血清清除率的预测非常困难且具有挑战性，因为它的发生率低，因此很难预测和定义HBsAg血清清除率，这是指在患有或未患有HBsAg抗体的情况下循环HBsAg的丧失。这项研究旨在开发和验证诺贝图，以预测CHB患者的HBsAg丢失。

方法：我们分析了总共1398例CHB患者。三分之二的患者被随机分配到训练集（n = 918），三分之一的患者被分配到验证集（n = 480）。使用训练集通过Cox回归分析进行单变量和多变量分析，并构造列线图。使用训练集和验证集进行区分和校准。

结果：在训练集的多变量分析中，将HBsAg丢失的独立因素包括BMI，HBeAg状态，HBsAg滴度（定量HBsAg）和基线乙型肝炎病毒（HBV）DNA水平纳入了诺模图。 HBsAg血清清除率校准曲线显示了诺模图预测与实际观察之间的最佳一致性。诺模图的一致性指数（C指数）为0.913，在验证集中确认，其中C指数为0.886。

结论：我们建立并验证了一种新颖的列线图，该图可以单独预测CHB患者的HBsAg血清清除率和非血清清除率，这在临床上是前所未有的。这种实用的预后模型可以帮助临床医生进行临床研究的决策和设计。

版权所有©2020 Jing Cao等。
利益冲突声明

没有为所有作者声明利益冲突。

StephenW

https://www.hindawi.com/journals/bmri/2020/6820179/