Real-time or dynamic non-invasive liver fibrosis testing for evaluating clinical prognoses and predicting chronic liver disease
10.3760/cma.j.cn501113-20250812-00323
- VernacularTitle:非侵入性肝纤维化检查对慢性肝病临床预后的评估与预测：实时还是动态
- Author:
Xinyu ZHAO
1
;
Yameng SUN
;
Yankun GAO
;
Zhengzhao LU
;
Cheng HUANG
;
Yuanyuan KONG
;
Jidong JIA
;
Hong YOU
Author Information
1. 首都医科大学附属北京友谊医院 临床流行病学与循证医学研究室，北京 100050
- Publication Type:Journal Article
- Keywords:
Liver fibrosis;
Non-invasive method;
Prognosis;
Chronic liver disease
- From:
Chinese Journal of Hepatology
2025;33(10):945-949
- CountryChina
- Language:Chinese
-
Abstract:
Liver fibrosis is a key histologic marker of long-term outcome in chronic liver disease. Non-invasive tests (NITs) have been shown to have predictive value, but the superiority of "dynamic" versus "static" assessment remains controversial. This article systematically reviews the latest evidence to elucidate the association between longitudinal changes in NITs and hepatic adverse events and assess the incremental contribution of dynamic monitoring to the model. Additionally, it reveals that the dynamic monitoring of NITs is truly superior to single evaluation, but the evidence is limited and the heterogeneity is significant. Dynamic modeling approaches for NITs require a shift from traditional parameter estimation to time-series machine learning. Future studies should make breakthroughs in disease stratification, modeling method innovation, data quality improvement, and prediction ability assessment so as to promote the transition of NITs from "static risk label" to "dynamic individualized engine," which can truly serve clinical decision-making.
