Ramy Younes1, Gian Paolo Caviglia2, Olivier Govaere3, Chiara Rosso2, Angelo Armandi2, Tiziana Sanavia2, Grazia Pennisi4, Antonio Liguori5, Paolo Francione6, Rocío Gallego-Durán7, Javier Ampuero7, Maria J Garcia Blanco8, Rocio Aller9, Dina Tiniakos10, Alastair Burt3, Ezio David11, Fabio M Vecchio12, Marco Maggioni13, Daniela Cabibi14, María Jesús Pareja15, Marco Y W Zaki16, Antonio Grieco17, Anna L Fracanzani6, Luca Valenti18, Luca Miele17, Piero Fariselli2, Salvatore Petta4, Manuel Romero-Gomez7, Quentin M Anstee19, Elisabetta Bugianesi20. 1. The Newcastle Liver Research Group, Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Boehringer Ingelheim International, GmbH, Ingelheim, Germany. 2. Department of Medical Sciences, Division of Gastroenterology and Hepatology, A.O. Città della Salute e della Scienza di Torino, University of Turin, Turin, Italy. 3. The Newcastle Liver Research Group, Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom. 4. Sezione di Gastroenterologia, PROMISE, Università di Palermo, Palermo, Italy. 5. Dipartimento Universitario Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy. 6. Unit of Medicine and Metabolic Disease Ca' Granda IRCCS Foundation, Policlinico Hospital, Department of Pathophysiology and Transplantation, University of Milan, Milan Italy. 7. UCM Digestive Diseases and SeLiver Group, Virgen del Rocio University Hospital, Institute of Biomedicine of Seville, University of Seville, Spain. 8. Hospital Universitario de La Princesa, Medicina Interna, Madrid, Spain. 9. Hospital Clínico de Valladolid, Valladolid, Spain. 10. The Newcastle Liver Research Group, Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Dept of Pathology, Aretaieion Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece. 11. Department of Pathology, Azienda Ospedaliero-Universitaria Città della Salute e della Scienza, University of Turin, Turin, Italy. 12. Dipartimento Universitario Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy; Area Anatomia Patologica. Fondazione Policlinico Gemelli IRCCS, Rome, Italy. 13. Department of Pathology, Ca' Granda IRCCS Foundation, Milan, Italy. 14. Pathology Institute, PROMISE, University of Palermo, Palermo, Italy. 15. Pathology Unit, Valme University Hospital, Seville, Spain. 16. The Newcastle Liver Research Group, Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Biochemistry Department, Faculty of Pharmacy, Minia University, Egypt. 17. Dipartimento Universitario Medicina e Chirurgia Traslazionale, Università Cattolica del Sacro Cuore, Rome, Italy; Area Medicina Interna, Gastroenterologia e Oncologia Medica, Fondazione Policlinico A. Gemelli IRCCS, Rome, Italy. 18. Translational Medicine, Department of Transfusion Medicine and Hematology, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy. 19. The Newcastle Liver Research Group, Translational & Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, United Kingdom; Newcastle NIHR Biomedical Research Centre, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, United Kingdom. Electronic address: quentin.anstee@ncl.ac.uk. 20. Department of Medical Sciences, Division of Gastroenterology and Hepatology, A.O. Città della Salute e della Scienza di Torino, University of Turin, Turin, Italy. Electronic address: elisabetta.bugianesi@unito.it.
Abstract
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.
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.
Authors: Diego Martínez-Urbistondo; RodrigoSan San Cristóbal; Paula Villares; Miguel Ángel Martínez-González; Nancy Babio; Dolores Corella; José Luis Del Val; José M Ordovás; Ángel M Alonso-Gómez; Julia Wärnberg; Jesús Vioque; Dora Romaguera; José López-Miranda; Ramon Estruch; Francisco J Tinahones; José Lapetra; J Luís Serra-Majem; Aurora Bueno-Cavanillas; Josep A Tur; Alba Marcos; Xavier Pintó; Miguel Delgado-Rodríguez; Pilar Matía-Martín; Josep Vidal; Clotilde Vázquez; Emilio Ros; María Vanessa Bullón Vela; Antoni Palau; Marta Masagué; Itziar Abete; Anai Moreno-Rodríguez; Inma Candela-García; Jadwiga Konieczna; Antonio García-Ríos; Oscar Lecea Juárez; Paco Martín; Albert Goday; M Ángeles Zulet; Jessica Vaquero-Luna; María Del Carmen Sayón Orea; Isabel Megías; Enric Baltasar; J Alfredo Martínez; Lidia Daimiel Journal: Front Endocrinol (Lausanne) Date: 2022-06-29 Impact factor: 6.055
Authors: Danielle A Scott; Mengjun Wang; Stephane Grauzam; Sarah Pippin; Alyson Black; Peggi M Angel; Richard R Drake; Stephen Castellino; Yuko Kono; Don C Rockey; Anand S Mehta Journal: Front Immunol Date: 2022-02-07 Impact factor: 8.786
Authors: Rodrigo Vieira Costa Lima; José Tadeu Stefano; Fernanda de Mello Malta; João Renato Rebello Pinho; Flair José Carrilho; Marco Arrese; Claudia P Oliveira Journal: Biomedicines Date: 2021-11-24