Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease
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 lo...
Gespeichert in:
| Veröffentlicht in: | Journal of hepatology 2021-10, Vol.75 (4), p.786-794 |
|---|---|
| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 794 |
|---|---|
| container_issue | 4 |
| container_start_page | 786 |
| container_title | Journal of hepatology |
| container_volume | 75 |
| creator | Younes, Ramy Caviglia, Gian Paolo Govaere, Olivier Rosso, Chiara Armandi, Angelo Sanavia, Tiziana Pennisi, Grazia Liguori, Antonio Francione, Paolo Gallego-Durán, Rocío Ampuero, Javier Garcia Blanco, Maria J. Aller, Rocio Tiniakos, Dina Burt, Alastair David, Ezio Vecchio, Fabio M. Maggioni, Marco Cabibi, Daniela Pareja, María Jesús Zaki, Marco Y.W. Grieco, Antonio Fracanzani, Anna L. Valenti, Luca Miele, Luca Fariselli, Piero Petta, Salvatore Romero-Gomez, Manuel Anstee, Quentin M. Bugianesi, Elisabetta |
| description | 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 |
| doi_str_mv | 10.1016/j.jhep.2021.05.008 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2538052208</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0168827821003433</els_id><sourcerecordid>2593193470</sourcerecordid><originalsourceid>FETCH-LOGICAL-c428t-ed8df8a0edbc86d39a1a491c84fe53b740bebdd20949a2aae7178ec70558643b3</originalsourceid><addsrcrecordid>eNp9kc-L1DAUgIMo7uzqP-BBAl68tL6kv1LwIouuwoAXPYc0ed1JaZOapCMD_vFmdlYPHjwFwvc-kvcR8opByYC176ZyOuBacuCshKYEEE_IjrUABbQ1e0p2GRKF4J24ItcxTgBQQV8_J1dVDT30XOzIr71390XCsFC_Je0XjFQ5Q9eAxupkj0jVYGebTtSP1HlXWHdU8XwftQ_W3dN4igmXSK2jq0oWXYr0p02HB1rN2h_8bDUdVcqSOU8GamxEFfEFeTaqOeLLx_OGfP_08dvt52L_9e7L7Yd9oWsuUoFGmFEoQDNo0ZqqV0zVPdOiHrGphq6GAQdjeP5br7hS2LFOoO6gaURbV0N1Q95evGvwPzaMSS42apxn5dBvUfKmEtBwDiKjb_5BJ78Fl1-Xqb5ifVV3kCl-oXTwMQYc5RrsosJJMpDnNnKS5zby3EZCI-FB_fpRvQ0Lmr8jf2Jk4P0FwLyLo8Ugo87r1LlEQJ2k8fZ__t-5oqJa</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2593193470</pqid></control><display><type>article</type><title>Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><creator>Younes, Ramy ; Caviglia, Gian Paolo ; Govaere, Olivier ; Rosso, Chiara ; Armandi, Angelo ; Sanavia, Tiziana ; Pennisi, Grazia ; Liguori, Antonio ; Francione, Paolo ; Gallego-Durán, Rocío ; Ampuero, Javier ; Garcia Blanco, Maria J. ; Aller, Rocio ; Tiniakos, Dina ; Burt, Alastair ; David, Ezio ; Vecchio, Fabio M. ; Maggioni, Marco ; Cabibi, Daniela ; Pareja, María Jesús ; Zaki, Marco Y.W. ; Grieco, Antonio ; Fracanzani, Anna L. ; Valenti, Luca ; Miele, Luca ; Fariselli, Piero ; Petta, Salvatore ; Romero-Gomez, Manuel ; Anstee, Quentin M. ; Bugianesi, Elisabetta</creator><creatorcontrib>Younes, Ramy ; Caviglia, Gian Paolo ; Govaere, Olivier ; Rosso, Chiara ; Armandi, Angelo ; Sanavia, Tiziana ; Pennisi, Grazia ; Liguori, Antonio ; Francione, Paolo ; Gallego-Durán, Rocío ; Ampuero, Javier ; Garcia Blanco, Maria J. ; Aller, Rocio ; Tiniakos, Dina ; Burt, Alastair ; David, Ezio ; Vecchio, Fabio M. ; Maggioni, Marco ; Cabibi, Daniela ; Pareja, María Jesús ; Zaki, Marco Y.W. ; Grieco, Antonio ; Fracanzani, Anna L. ; Valenti, Luca ; Miele, Luca ; Fariselli, Piero ; Petta, Salvatore ; Romero-Gomez, Manuel ; Anstee, Quentin M. ; Bugianesi, Elisabetta</creatorcontrib><description>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.
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.
[Display omitted]
•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.</description><identifier>ISSN: 0168-8278</identifier><identifier>EISSN: 1600-0641</identifier><identifier>DOI: 10.1016/j.jhep.2021.05.008</identifier><identifier>PMID: 34090928</identifier><language>eng</language><publisher>Netherlands: Elsevier B.V</publisher><subject>Adult ; APRI ; Area Under Curve ; BARD ; Cirrhosis ; Cross-Sectional Studies ; Death ; Fatty liver ; Female ; FIB-4 ; Fibrosis ; Hepatocellular carcinoma ; HFS ; Humans ; Liver - pathology ; Liver cancer ; Liver cirrhosis ; Liver diseases ; Male ; Middle Aged ; Mortality ; NASH ; NFS ; Non-alcoholic Fatty Liver Disease - complications ; Non-alcoholic Fatty Liver Disease - mortality ; NSS ; Patients ; Predictions ; Predictive Value of Tests ; Prognosis ; Reproducibility of Results ; Research Design - standards ; Research Design - trends ; ROC Curve ; Severity of Illness Index ; Time</subject><ispartof>Journal of hepatology, 2021-10, Vol.75 (4), p.786-794</ispartof><rights>2021 European Association for the Study of the Liver</rights><rights>Copyright © 2021 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.</rights><rights>Copyright Elsevier Science Ltd. Oct 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c428t-ed8df8a0edbc86d39a1a491c84fe53b740bebdd20949a2aae7178ec70558643b3</citedby><cites>FETCH-LOGICAL-c428t-ed8df8a0edbc86d39a1a491c84fe53b740bebdd20949a2aae7178ec70558643b3</cites><orcidid>0000-0002-8332-2122 ; 0000-0001-6518-7089 ; 0000-0003-1300-3027 ; 0000-0003-3464-0068 ; 0000-0003-3288-0631 ; 0000-0002-6795-4541 ; 0000-0003-3097-5776 ; 0000-0002-9224-1914 ; 0000-0001-8909-0345 ; 0000-0002-7245-4445 ; 0000-0002-4426-6930 ; 0000-0003-4657-7780 ; 0000-0002-0529-9481 ; 0000-0002-0577-0018 ; 0000-0001-6571-6577 ; 0000-0002-0801-7152</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jhep.2021.05.008$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/34090928$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Younes, Ramy</creatorcontrib><creatorcontrib>Caviglia, Gian Paolo</creatorcontrib><creatorcontrib>Govaere, Olivier</creatorcontrib><creatorcontrib>Rosso, Chiara</creatorcontrib><creatorcontrib>Armandi, Angelo</creatorcontrib><creatorcontrib>Sanavia, Tiziana</creatorcontrib><creatorcontrib>Pennisi, Grazia</creatorcontrib><creatorcontrib>Liguori, Antonio</creatorcontrib><creatorcontrib>Francione, Paolo</creatorcontrib><creatorcontrib>Gallego-Durán, Rocío</creatorcontrib><creatorcontrib>Ampuero, Javier</creatorcontrib><creatorcontrib>Garcia Blanco, Maria J.</creatorcontrib><creatorcontrib>Aller, Rocio</creatorcontrib><creatorcontrib>Tiniakos, Dina</creatorcontrib><creatorcontrib>Burt, Alastair</creatorcontrib><creatorcontrib>David, Ezio</creatorcontrib><creatorcontrib>Vecchio, Fabio M.</creatorcontrib><creatorcontrib>Maggioni, Marco</creatorcontrib><creatorcontrib>Cabibi, Daniela</creatorcontrib><creatorcontrib>Pareja, María Jesús</creatorcontrib><creatorcontrib>Zaki, Marco Y.W.</creatorcontrib><creatorcontrib>Grieco, Antonio</creatorcontrib><creatorcontrib>Fracanzani, Anna L.</creatorcontrib><creatorcontrib>Valenti, Luca</creatorcontrib><creatorcontrib>Miele, Luca</creatorcontrib><creatorcontrib>Fariselli, Piero</creatorcontrib><creatorcontrib>Petta, Salvatore</creatorcontrib><creatorcontrib>Romero-Gomez, Manuel</creatorcontrib><creatorcontrib>Anstee, Quentin M.</creatorcontrib><creatorcontrib>Bugianesi, Elisabetta</creatorcontrib><title>Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease</title><title>Journal of hepatology</title><addtitle>J Hepatol</addtitle><description>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.
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.
[Display omitted]
•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.</description><subject>Adult</subject><subject>APRI</subject><subject>Area Under Curve</subject><subject>BARD</subject><subject>Cirrhosis</subject><subject>Cross-Sectional Studies</subject><subject>Death</subject><subject>Fatty liver</subject><subject>Female</subject><subject>FIB-4</subject><subject>Fibrosis</subject><subject>Hepatocellular carcinoma</subject><subject>HFS</subject><subject>Humans</subject><subject>Liver - pathology</subject><subject>Liver cancer</subject><subject>Liver cirrhosis</subject><subject>Liver diseases</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Mortality</subject><subject>NASH</subject><subject>NFS</subject><subject>Non-alcoholic Fatty Liver Disease - complications</subject><subject>Non-alcoholic Fatty Liver Disease - mortality</subject><subject>NSS</subject><subject>Patients</subject><subject>Predictions</subject><subject>Predictive Value of Tests</subject><subject>Prognosis</subject><subject>Reproducibility of Results</subject><subject>Research Design - standards</subject><subject>Research Design - trends</subject><subject>ROC Curve</subject><subject>Severity of Illness Index</subject><subject>Time</subject><issn>0168-8278</issn><issn>1600-0641</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc-L1DAUgIMo7uzqP-BBAl68tL6kv1LwIouuwoAXPYc0ed1JaZOapCMD_vFmdlYPHjwFwvc-kvcR8opByYC176ZyOuBacuCshKYEEE_IjrUABbQ1e0p2GRKF4J24ItcxTgBQQV8_J1dVDT30XOzIr71390XCsFC_Je0XjFQ5Q9eAxupkj0jVYGebTtSP1HlXWHdU8XwftQ_W3dN4igmXSK2jq0oWXYr0p02HB1rN2h_8bDUdVcqSOU8GamxEFfEFeTaqOeLLx_OGfP_08dvt52L_9e7L7Yd9oWsuUoFGmFEoQDNo0ZqqV0zVPdOiHrGphq6GAQdjeP5br7hS2LFOoO6gaURbV0N1Q95evGvwPzaMSS42apxn5dBvUfKmEtBwDiKjb_5BJ78Fl1-Xqb5ifVV3kCl-oXTwMQYc5RrsosJJMpDnNnKS5zby3EZCI-FB_fpRvQ0Lmr8jf2Jk4P0FwLyLo8Ugo87r1LlEQJ2k8fZ__t-5oqJa</recordid><startdate>202110</startdate><enddate>202110</enddate><creator>Younes, Ramy</creator><creator>Caviglia, Gian Paolo</creator><creator>Govaere, Olivier</creator><creator>Rosso, Chiara</creator><creator>Armandi, Angelo</creator><creator>Sanavia, Tiziana</creator><creator>Pennisi, Grazia</creator><creator>Liguori, Antonio</creator><creator>Francione, Paolo</creator><creator>Gallego-Durán, Rocío</creator><creator>Ampuero, Javier</creator><creator>Garcia Blanco, Maria J.</creator><creator>Aller, Rocio</creator><creator>Tiniakos, Dina</creator><creator>Burt, Alastair</creator><creator>David, Ezio</creator><creator>Vecchio, Fabio M.</creator><creator>Maggioni, Marco</creator><creator>Cabibi, Daniela</creator><creator>Pareja, María Jesús</creator><creator>Zaki, Marco Y.W.</creator><creator>Grieco, Antonio</creator><creator>Fracanzani, Anna L.</creator><creator>Valenti, Luca</creator><creator>Miele, Luca</creator><creator>Fariselli, Piero</creator><creator>Petta, Salvatore</creator><creator>Romero-Gomez, Manuel</creator><creator>Anstee, Quentin M.</creator><creator>Bugianesi, Elisabetta</creator><general>Elsevier B.V</general><general>Elsevier Science Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7T5</scope><scope>H94</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-8332-2122</orcidid><orcidid>https://orcid.org/0000-0001-6518-7089</orcidid><orcidid>https://orcid.org/0000-0003-1300-3027</orcidid><orcidid>https://orcid.org/0000-0003-3464-0068</orcidid><orcidid>https://orcid.org/0000-0003-3288-0631</orcidid><orcidid>https://orcid.org/0000-0002-6795-4541</orcidid><orcidid>https://orcid.org/0000-0003-3097-5776</orcidid><orcidid>https://orcid.org/0000-0002-9224-1914</orcidid><orcidid>https://orcid.org/0000-0001-8909-0345</orcidid><orcidid>https://orcid.org/0000-0002-7245-4445</orcidid><orcidid>https://orcid.org/0000-0002-4426-6930</orcidid><orcidid>https://orcid.org/0000-0003-4657-7780</orcidid><orcidid>https://orcid.org/0000-0002-0529-9481</orcidid><orcidid>https://orcid.org/0000-0002-0577-0018</orcidid><orcidid>https://orcid.org/0000-0001-6571-6577</orcidid><orcidid>https://orcid.org/0000-0002-0801-7152</orcidid></search><sort><creationdate>202110</creationdate><title>Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease</title><author>Younes, Ramy ; Caviglia, Gian Paolo ; Govaere, Olivier ; Rosso, Chiara ; Armandi, Angelo ; Sanavia, Tiziana ; Pennisi, Grazia ; Liguori, Antonio ; Francione, Paolo ; Gallego-Durán, Rocío ; Ampuero, Javier ; Garcia Blanco, Maria J. ; Aller, Rocio ; Tiniakos, Dina ; Burt, Alastair ; David, Ezio ; Vecchio, Fabio M. ; Maggioni, Marco ; Cabibi, Daniela ; Pareja, María Jesús ; Zaki, Marco Y.W. ; Grieco, Antonio ; Fracanzani, Anna L. ; Valenti, Luca ; Miele, Luca ; Fariselli, Piero ; Petta, Salvatore ; Romero-Gomez, Manuel ; Anstee, Quentin M. ; Bugianesi, Elisabetta</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c428t-ed8df8a0edbc86d39a1a491c84fe53b740bebdd20949a2aae7178ec70558643b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Adult</topic><topic>APRI</topic><topic>Area Under Curve</topic><topic>BARD</topic><topic>Cirrhosis</topic><topic>Cross-Sectional Studies</topic><topic>Death</topic><topic>Fatty liver</topic><topic>Female</topic><topic>FIB-4</topic><topic>Fibrosis</topic><topic>Hepatocellular carcinoma</topic><topic>HFS</topic><topic>Humans</topic><topic>Liver - pathology</topic><topic>Liver cancer</topic><topic>Liver cirrhosis</topic><topic>Liver diseases</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Mortality</topic><topic>NASH</topic><topic>NFS</topic><topic>Non-alcoholic Fatty Liver Disease - complications</topic><topic>Non-alcoholic Fatty Liver Disease - mortality</topic><topic>NSS</topic><topic>Patients</topic><topic>Predictions</topic><topic>Predictive Value of Tests</topic><topic>Prognosis</topic><topic>Reproducibility of Results</topic><topic>Research Design - standards</topic><topic>Research Design - trends</topic><topic>ROC Curve</topic><topic>Severity of Illness Index</topic><topic>Time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Younes, Ramy</creatorcontrib><creatorcontrib>Caviglia, Gian Paolo</creatorcontrib><creatorcontrib>Govaere, Olivier</creatorcontrib><creatorcontrib>Rosso, Chiara</creatorcontrib><creatorcontrib>Armandi, Angelo</creatorcontrib><creatorcontrib>Sanavia, Tiziana</creatorcontrib><creatorcontrib>Pennisi, Grazia</creatorcontrib><creatorcontrib>Liguori, Antonio</creatorcontrib><creatorcontrib>Francione, Paolo</creatorcontrib><creatorcontrib>Gallego-Durán, Rocío</creatorcontrib><creatorcontrib>Ampuero, Javier</creatorcontrib><creatorcontrib>Garcia Blanco, Maria J.</creatorcontrib><creatorcontrib>Aller, Rocio</creatorcontrib><creatorcontrib>Tiniakos, Dina</creatorcontrib><creatorcontrib>Burt, Alastair</creatorcontrib><creatorcontrib>David, Ezio</creatorcontrib><creatorcontrib>Vecchio, Fabio M.</creatorcontrib><creatorcontrib>Maggioni, Marco</creatorcontrib><creatorcontrib>Cabibi, Daniela</creatorcontrib><creatorcontrib>Pareja, María Jesús</creatorcontrib><creatorcontrib>Zaki, Marco Y.W.</creatorcontrib><creatorcontrib>Grieco, Antonio</creatorcontrib><creatorcontrib>Fracanzani, Anna L.</creatorcontrib><creatorcontrib>Valenti, Luca</creatorcontrib><creatorcontrib>Miele, Luca</creatorcontrib><creatorcontrib>Fariselli, Piero</creatorcontrib><creatorcontrib>Petta, Salvatore</creatorcontrib><creatorcontrib>Romero-Gomez, Manuel</creatorcontrib><creatorcontrib>Anstee, Quentin M.</creatorcontrib><creatorcontrib>Bugianesi, Elisabetta</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of hepatology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Younes, Ramy</au><au>Caviglia, Gian Paolo</au><au>Govaere, Olivier</au><au>Rosso, Chiara</au><au>Armandi, Angelo</au><au>Sanavia, Tiziana</au><au>Pennisi, Grazia</au><au>Liguori, Antonio</au><au>Francione, Paolo</au><au>Gallego-Durán, Rocío</au><au>Ampuero, Javier</au><au>Garcia Blanco, Maria J.</au><au>Aller, Rocio</au><au>Tiniakos, Dina</au><au>Burt, Alastair</au><au>David, Ezio</au><au>Vecchio, Fabio M.</au><au>Maggioni, Marco</au><au>Cabibi, Daniela</au><au>Pareja, María Jesús</au><au>Zaki, Marco Y.W.</au><au>Grieco, Antonio</au><au>Fracanzani, Anna L.</au><au>Valenti, Luca</au><au>Miele, Luca</au><au>Fariselli, Piero</au><au>Petta, Salvatore</au><au>Romero-Gomez, Manuel</au><au>Anstee, Quentin M.</au><au>Bugianesi, Elisabetta</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease</atitle><jtitle>Journal of hepatology</jtitle><addtitle>J Hepatol</addtitle><date>2021-10</date><risdate>2021</risdate><volume>75</volume><issue>4</issue><spage>786</spage><epage>794</epage><pages>786-794</pages><issn>0168-8278</issn><eissn>1600-0641</eissn><abstract>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.
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.
[Display omitted]
•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.</abstract><cop>Netherlands</cop><pub>Elsevier B.V</pub><pmid>34090928</pmid><doi>10.1016/j.jhep.2021.05.008</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0002-8332-2122</orcidid><orcidid>https://orcid.org/0000-0001-6518-7089</orcidid><orcidid>https://orcid.org/0000-0003-1300-3027</orcidid><orcidid>https://orcid.org/0000-0003-3464-0068</orcidid><orcidid>https://orcid.org/0000-0003-3288-0631</orcidid><orcidid>https://orcid.org/0000-0002-6795-4541</orcidid><orcidid>https://orcid.org/0000-0003-3097-5776</orcidid><orcidid>https://orcid.org/0000-0002-9224-1914</orcidid><orcidid>https://orcid.org/0000-0001-8909-0345</orcidid><orcidid>https://orcid.org/0000-0002-7245-4445</orcidid><orcidid>https://orcid.org/0000-0002-4426-6930</orcidid><orcidid>https://orcid.org/0000-0003-4657-7780</orcidid><orcidid>https://orcid.org/0000-0002-0529-9481</orcidid><orcidid>https://orcid.org/0000-0002-0577-0018</orcidid><orcidid>https://orcid.org/0000-0001-6571-6577</orcidid><orcidid>https://orcid.org/0000-0002-0801-7152</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0168-8278 |
| ispartof | Journal of hepatology, 2021-10, Vol.75 (4), p.786-794 |
| issn | 0168-8278 1600-0641 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2538052208 |
| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Adult APRI Area Under Curve BARD Cirrhosis Cross-Sectional Studies Death Fatty liver Female FIB-4 Fibrosis Hepatocellular carcinoma HFS Humans Liver - pathology Liver cancer Liver cirrhosis Liver diseases Male Middle Aged Mortality NASH NFS Non-alcoholic Fatty Liver Disease - complications Non-alcoholic Fatty Liver Disease - mortality NSS Patients Predictions Predictive Value of Tests Prognosis Reproducibility of Results Research Design - standards Research Design - trends ROC Curve Severity of Illness Index Time |
| title | Long-term outcomes and predictive ability of non-invasive scoring systems in patients with non-alcoholic fatty liver disease |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-20T16%3A52%3A50IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Long-term%20outcomes%20and%20predictive%20ability%20of%20non-invasive%20scoring%20systems%20in%20patients%20with%20non-alcoholic%20fatty%20liver%20disease&rft.jtitle=Journal%20of%20hepatology&rft.au=Younes,%20Ramy&rft.date=2021-10&rft.volume=75&rft.issue=4&rft.spage=786&rft.epage=794&rft.pages=786-794&rft.issn=0168-8278&rft.eissn=1600-0641&rft_id=info:doi/10.1016/j.jhep.2021.05.008&rft_dat=%3Cproquest_cross%3E2593193470%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2593193470&rft_id=info:pmid/34090928&rft_els_id=S0168827821003433&rfr_iscdi=true |