新型慢性乙型肝炎患者肝纤维化的预测模型

StephenW

A Novel Prediction Model for Significant Liver Fibrosis in Patients with Chronic Hepatitis B
Yaqiong Chen  1 , Jiao Gong  1 , Wenying Zhou  1 , Yusheng Jie  2 , Zhaoxia Li  1 , Yutian Chong  2 , Bo Hu  1
Affiliations
Affiliations

    1
    Department of Laboratory Medicine, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
    2
    Department of Infectious Diseases, Key Laboratory of Liver Disease of Guangdong Province, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

    PMID: 32695818 PMCID: PMC7368191 DOI: 10.1155/2020/6839137

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Abstract

Background: Preventing liver fibrosis from progressing to cirrhosis and even liver cancer is a key step in the treatment of chronic hepatitis B (CHB). This study is aimed at constructing and validating a new nomogram for predicting significant liver fibrosis (S ≥ 2) in CHB patients.

Methods: The nomogram was based on a retrospective study of 252 CHB patients. The predictive accuracy and discriminative ability of the nomogram were evaluated by the area under receiver operating characteristic curve (AUROC), decision curves, and calibration curve compared with the fibrosis 4 score (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI). The results were validated using bootstrap resampling and an external set of 168 CHB patients.

Results: A total of 420 CHB patients were enrolled based on liver biopsy results. Independent factors predicting significant liver fibrosis were laminin (LN), procollagen type III N-terminal peptide (PIIINP), and blood platelet count (PLT) in a multivariate analysis, and these factors were selected to construct the nomogram. The calibration curve for the probability of significant liver fibrosis showed optimal agreement between the prediction from the nomogram and actual observation. The prediction from the nomogram was more consistent with the results of liver biopsy than FIB-4 and APRI. The AUROC of the nomogram was higher than that of FIB-4 and APRI for predicting significant liver fibrosis. These results were confirmed in the validation set. Furthermore, the decision curve analysis suggested that the most net benefits were provided by the nomogram.

Conclusions: We found the proposed nomogram resulted in a more accurate prediction of significant liver fibrosis in CHB patients and could provide the most net benefits. We recommend this noninvasive assessment for patients with liver fibrosis to avoid the risk of liver biopsy and earlier intervention to prevent the development of cirrhosis or liver cancer.

Copyright © 2020 Yaqiong Chen et al.

StephenW

新型慢性乙型肝炎患者肝纤维化的预测模型
陈亚琼1，脚弓1，周雯莹1，俞胜杰2，李朝霞1，俞天冲2，博虎1
隶属关系
隶属关系

    1个
    中山大学附属第三医院检验医学科，广州
    2
    中山大学附属第三医院广东省肝病重点实验室，广东省传染病科。

    PMID：32695818 PMCID：PMC7368191 DOI：10.1155 / 2020/6839137

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抽象

背景：预防肝纤维化发展为肝硬化甚至肝癌是治疗慢性乙型肝炎（CHB）的关键步骤。这项研究旨在构建和验证新的列线图，以预测CHB患者的严重肝纤维化（S≥2）。

方法：列线图基于对252名CHB患者的回顾性研究。诺模图的预测准确性和判别能力通过与接收器工作特征曲线（AUROC），决策曲线和校正曲线下的面积进行比较，并与纤维化4评分（FIB-4）和天冬氨酸转氨酶与血小板比率指数（ 4月）。使用引导程序重采样和外部168位CHB患者对结果进行了验证。

结果：根据肝活检结果，总共招募了420名CHB患者。在多变量分析中，预测严重肝纤维化的独立因素是层粘连蛋白（LN），III型胶原原N末端肽（PIIINP）和血小板计数（PLT），并选择这些因素来构建列线图。严重肝纤维化可能性的校准曲线显示出诺模图预测与实际观察之间的最佳一致性。从诺模图的预测与肝活检的结果比FIB -4和APRI更一致。诺模图的AUROC高于FIB-4和APRI，可预测明显的肝纤维化。这些结果在验证集中得到确认。此外，决策曲线分析表明，诺模图提供了最大的净收益。

结论：我们发现拟议的诺模图可以更准确地预测CHB患者的重大肝纤维化，并且可以提供最大的净收益。我们建议对肝纤维化患者进行这种非侵入性评估，以避免发生肝活检的风险，并尽早干预以预防肝硬化或肝癌的发展。

版权所有©2020 Yaqiong Chen等。

StephenW

http://downloads.hindawi.com/journals/bmri/2020/6839137.pdf