Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease

医学 内科学 脂肪肝 肝硬化 胃肠病学 队列 危险系数 比例危险模型 一致性 纤维化 疾病 置信区间
作者
Ramy Younes,Gian Paolo Caviglia,Olivier Govaere,Chiara Rosso,Angelo Armandi,Tiziana Sanavia,Grazia Pennisi,Antonio Liguori,Paolo Francione,Rocío Gallego‐Durán,Javier Ampuero,Marı́a José Blanco,R. Aller,Dina Tiniakos,Alastair D. Burt,Ezio David,Fabio Maria Vecchio,Marco Maggioni,Daniela Cabibi,María Jesús Pareja,Marco Y. W. Zaki,Antonio Grieco,Anna Ludovica Fracanzani,Luca Valenti,Luca Miele,Piero Fariselli,Salvatore Petta,Manuel Romero‐Gómez,Quentin M. Anstee,Elisabetta Bugianesi
出处
期刊:Journal of Hepatology [Elsevier]
卷期号:75 (4): 786-794 被引量:125
标识
DOI:10.1016/j.jhep.2021.05.008
摘要

•Different non-invasive scoring systems (NSS) have been proposed to stratify patients according to the risk of advanced fibrosis. •In the cross-sectional analysis, HFS showed the best performance for the identification of advanced fibrosis. •NFS and FIB-4 showed the best performance for the detection of histological cirrhosis. •After a median follow-up of ~7 years, NFS, HFS and FIB-4 performed similarly well for the prediction of HCC and overall mortality. •All NSS had limited performance for extrahepatic events, although those incorporating diabetes performed slightly better. Background & Aims Non-invasive scoring systems (NSS) are used to identify patients with non-alcoholic fatty liver disease (NAFLD) who are at risk of advanced fibrosis, but their reliability in predicting long-term outcomes for hepatic/extrahepatic complications or death and their concordance in cross-sectional and longitudinal risk stratification remain uncertain. Methods The most common NSS (NFS, FIB-4, BARD, APRI) and the Hepamet fibrosis score (HFS) were assessed in 1,173 European patients with NAFLD from tertiary centres. Performance for fibrosis risk stratification and for the prediction of long-term hepatic/extrahepatic events, hepatocarcinoma (HCC) and overall mortality were evaluated in terms of AUC and Harrell’s c-index. For longitudinal data, NSS-based Cox proportional hazard models were trained on the whole cohort with repeated 5-fold cross-validation, sampling for testing from the 607 patients with all NSS available. Results Cross-sectional analysis revealed HFS as the best performer for the identification of significant (F0-1 vs. F2-4, AUC = 0.758) and advanced (F0-2 vs. F3-4, AUC = 0.805) fibrosis, while NFS and FIB-4 showed the best performance for detecting histological cirrhosis (range AUCs 0.85-0.88). Considering longitudinal data (follow-up between 62 and 110 months), NFS and FIB-4 were the best at predicting liver-related events (c-indices>0.7), NFS for HCC (c-index = 0.9 on average), and FIB-4 and HFS for overall mortality (c-indices >0.8). All NSS showed limited performance (c-indices <0.7) for extrahepatic events. Conclusions Overall, NFS, HFS and FIB-4 outperformed APRI and BARD for both cross-sectional identification of fibrosis and prediction of long-term outcomes, confirming that they are useful tools for the clinical management of patients with NAFLD at increased risk of fibrosis and liver-related complications or death. Lay summary Non-invasive scoring systems are increasingly being used in patients with non-alcoholic fatty liver disease to identify those at risk of advanced fibrosis and hence clinical complications. Herein, we compared various non-invasive scoring systems and identified those that were best at identifying risk, as well as those that were best for the prediction of long-term outcomes, such as liver-related events, liver cancer and death. Non-invasive scoring systems (NSS) are used to identify patients with non-alcoholic fatty liver disease (NAFLD) who are at risk of advanced fibrosis, but their reliability in predicting long-term outcomes for hepatic/extrahepatic complications or death and their concordance in cross-sectional and longitudinal risk stratification remain uncertain. The most common NSS (NFS, FIB-4, BARD, APRI) and the Hepamet fibrosis score (HFS) were assessed in 1,173 European patients with NAFLD from tertiary centres. Performance for fibrosis risk stratification and for the prediction of long-term hepatic/extrahepatic events, hepatocarcinoma (HCC) and overall mortality were evaluated in terms of AUC and Harrell’s c-index. For longitudinal data, NSS-based Cox proportional hazard models were trained on the whole cohort with repeated 5-fold cross-validation, sampling for testing from the 607 patients with all NSS available. Cross-sectional analysis revealed HFS as the best performer for the identification of significant (F0-1 vs. F2-4, AUC = 0.758) and advanced (F0-2 vs. F3-4, AUC = 0.805) fibrosis, while NFS and FIB-4 showed the best performance for detecting histological cirrhosis (range AUCs 0.85-0.88). Considering longitudinal data (follow-up between 62 and 110 months), NFS and FIB-4 were the best at predicting liver-related events (c-indices>0.7), NFS for HCC (c-index = 0.9 on average), and FIB-4 and HFS for overall mortality (c-indices >0.8). All NSS showed limited performance (c-indices <0.7) for extrahepatic events. Overall, NFS, HFS and FIB-4 outperformed APRI and BARD for both cross-sectional identification of fibrosis and prediction of long-term outcomes, confirming that they are useful tools for the clinical management of patients with NAFLD at increased risk of fibrosis and liver-related complications or death.
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