Department of Infectious Diseases and Clinical Microbiology, Abant Izzet Baysal University Faculty of Medicine, Bolu, Turkey.
Acta Gastroenterol Belg. 2024 Jul-Sep;87(3):388-392. doi: 10.51821/87.3.13290.
BACKGROUND & AIMS: Chronic hepatitis B is still a major cause of morbidity and mortality worldwide. In recent years, there has been increasing research on inexpensive, noninvasive, reproducible methods for detecting fibrosis in the liver. In this study, we examined the efficacy of 15 different noninvasive fibrosis markers for predicting significant liver fibrosis in chronic hepatitis B patients.
Patients who underwent liver biopsy for chronic hepatitis B between 01.01.2010 and 01.01.2022 were retrospectively analysed. The study population was divided into two groups according to significant fibrosis (F≥3). Receiver operating characteristic analysis was performed to examine the diagnostic performance of these noninvasive fibrosis markers for the prediction of significant fibrosis. Multiple logistic regression analysis was used create a model which predicts significant fibrosis better than the individual markers.
In total, 234 chronic hepatitis B patients were enrolled in this study. Among the 15 noninvasive fibrosis markers, King's score was found to have the biggest AUC in predicting significant fibrosis (F≥3). Furthermore, a model containing King's score, GUCI and GPR has the ability of prediction of significant fibrosis better than every individual marker (cut-off of the model >0,3356, p<0.0001).
According to our study results, the model containing King's score, GUCI and GPR can be used to predict significant liver fibrosis in chronic hepatitis B patients followed-up in countries with limited sources.
慢性乙型肝炎仍然是全球发病率和死亡率的主要原因。近年来,人们越来越关注廉价、非侵入性、可重复的方法来检测肝脏纤维化。在这项研究中,我们研究了 15 种不同的无创性纤维化标志物在预测慢性乙型肝炎患者显著肝纤维化中的疗效。
回顾性分析了 2010 年 1 月 1 日至 2022 年 1 月 1 日期间因慢性乙型肝炎行肝活检的患者。根据显著纤维化(F≥3)将研究人群分为两组。采用受试者工作特征分析(receiver operating characteristic analysis)评估这些无创性纤维化标志物对预测显著纤维化的诊断性能。采用多因素逻辑回归分析创建一个能比单个标志物更好地预测显著纤维化的模型。
本研究共纳入 234 例慢性乙型肝炎患者。在 15 种无创性纤维化标志物中,King 评分在预测显著纤维化(F≥3)方面具有最大的 AUC。此外,包含 King 评分、GUCI 和 GPR 的模型在预测显著纤维化方面优于每个单独的标志物(模型截断值>0.3356,p<0.0001)。
根据我们的研究结果,在资源有限的国家,包含 King 评分、GUCI 和 GPR 的模型可用于预测慢性乙型肝炎患者的显著肝纤维化。