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多中心验证 FIB-6 作为一种新的机器学习非侵入性评分,以排除经活检证实的 MAFLD 中的肝硬化。

Multicenter validation of FIB-6 as a novel machine learning non-invasive score to rule out liver cirrhosis in biopsy-proven MAFLD.

机构信息

Digestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran.

Liver Disease Research Center, Department of Medicine, College of Medicine, King Saud University, Riyadh, Kingdom of Saudi Arabia.

出版信息

Eur J Gastroenterol Hepatol. 2023 Nov 1;35(11):1284-1288. doi: 10.1097/MEG.0000000000002641. Epub 2023 Sep 5.

DOI:10.1097/MEG.0000000000002641
PMID:37695595
Abstract

BACKGROUND AND AIMS

We previously developed and validated a non-invasive diagnostic index based on routine laboratory parameters for predicting the stage of hepatic fibrosis in patients with chronic hepatitis C (CHC) called FIB-6 through machine learning with random forests algorithm using retrospective data of 7238 biopsy-proven CHC patients. Our aim is to validate this novel score in patients with metabolic dysfunction-associated fatty liver disease (MAFLD).

METHOD

Performance of the new score was externally validated in cohorts from one site in Egypt (n = 674) and in 5 different countries (n = 1798) in Iran, KSA, Greece, Turkey and Oman. Experienced pathologists using METAVIR scoring system scored the biopsy samples. Results were compared with FIB-4, APRI, and AAR.

RESULTS

A total of 2472 and their liver biopsy results were included, using the optimal cutoffs of FIB-6 indicated a reliable performance in diagnosing cirrhosis, severe fibrosis, and significant fibrosis with sensitivity = 70.5%, specificity = 62.9%. PPV = 15.0% and NPV = 95.8% for diagnosis of cirrhosis. For diagnosis of severe fibrosis (F3 and F4), the results were 86.5%, 24.0%, 15.1% and 91.9% respectively, while for diagnosis of significant fibrosis (F2, F3 and F4), the results were 87.0%, 16.4%, 24.8% and 80.0%). Comparing the results of FIB-6 rule-out cutoffs with those of FIB-4, APRI, and AAR, FIB-6 had the highest sensitivity and NPV (97.0% and 94.7%), as compared to FIB-4 (71.6% and 94.7%), APRI (36.4% and 90.7%), and AAR (61.2% and 90.9%).

CONCLUSION

FIB-6 score is an accurate, simple, NIT for ruling out advanced fibrosis and liver cirrhosis in patients with MAFLD.

摘要

背景与目的

我们先前使用随机森林算法基于常规实验室参数开发并验证了一种用于预测慢性丙型肝炎(CHC)患者肝纤维化分期的非侵入性诊断指数,称为 FIB-6,该研究基于回顾性数据,纳入了 7238 例经活检证实的 CHC 患者。本研究旨在对代谢相关脂肪性肝病(MAFLD)患者进行该新评分的验证。

方法

该新评分在埃及一个地点的两个队列(n=674)和 5 个不同国家(伊朗、沙特阿拉伯、希腊、土耳其和阿曼,n=1798)中进行外部验证,经验丰富的病理学家使用 METAVIR 评分系统对活检样本进行评分。结果与 FIB-4、APRI 和 AAR 进行比较。

结果

共纳入 2472 例患者及其肝活检结果,使用 FIB-6 的最佳截断值可可靠地诊断肝硬化、严重纤维化和显著纤维化,其诊断肝硬化的敏感性=70.5%,特异性=62.9%。对肝硬化的阳性预测值(PPV)为 15.0%,阴性预测值(NPV)为 95.8%。对严重纤维化(F3 和 F4)的诊断结果分别为 86.5%、24.0%、15.1%和 91.9%,对显著纤维化(F2、F3 和 F4)的诊断结果分别为 87.0%、16.4%、24.8%和 80.0%。与 FIB-4、APRI 和 AAR 的排除截断值相比,FIB-6 的敏感性和 NPV 最高(97.0%和 94.7%),而 FIB-4 的敏感性和 NPV 分别为 71.6%和 94.7%、APRI 为 36.4%和 90.7%,AAR 为 61.2%和 90.9%。

结论

FIB-6 评分是一种准确、简单的非侵入性方法,可用于排除 MAFLD 患者的晚期纤维化和肝硬化。

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