Multicenter validation of FIB-6 as a novel machine learning non-invasive score to rule out liver cirrhosis in biopsy-proven MAFLD
dc.authorid | 0000-0002-8909-2102 | en_US |
dc.authorscopusid | 56035868800 | en_US |
dc.authorwosid | K-1194-2018 | en_US |
dc.contributor.author | Anushiravani, Amir | |
dc.contributor.author | Alswat, Khalid | |
dc.contributor.author | Dalekos, George N. | |
dc.contributor.author | Zachou, Kalliopi | |
dc.contributor.author | Örmeci, Necati | |
dc.contributor.author | Al-Busafi, Said | |
dc.contributor.author | Abdo, Ayman | |
dc.contributor.author | Sanai, Faisal | |
dc.contributor.author | Mikhail, Nabiel Nh | |
dc.contributor.author | Soliman, Riham | |
dc.contributor.author | Shiha, Gamal | |
dc.date.accessioned | 2023-09-14T11:51:18Z | |
dc.date.available | 2023-09-14T11:51:18Z | |
dc.date.issued | 2023 | en_US |
dc.department | Fakülteler, Tıp Fakültesi, Dahili Tıp Bilimleri Bölümü, İç Hastalıkları Ana Bilim Dalı | en_US |
dc.description.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. | en_US |
dc.identifier.citation | Anushiravani, A., Alswat, K., Dalekos, G. N., Zachou, K., Örmeci, N., Al-Busafi, S., Abdo, A., Sanai, F., Mikhail, N.N., Soliman, R., & Shiha, G. (2023). Multicenter validation of FIB-6 as a novel machine learning non-invasive score to rule out liver cirrhosis in biopsy-proven MAFLD. European Journal of Gastroenterology & Hepatology, 35(11), pp. 1284-1288. https://doi.org/10.1097/MEG.0000000000002641 | en_US |
dc.identifier.doi | 10.1097/MEG.0000000000002641 | en_US |
dc.identifier.endpage | 1288 | en_US |
dc.identifier.issn | 0954-691X | |
dc.identifier.issn | 1473-5687 | |
dc.identifier.issue | 11 | en_US |
dc.identifier.pmid | PMID: 37695595 | en_US |
dc.identifier.scopus | 2-s2.0-85174315035 | en_US |
dc.identifier.scopusquality | Q2 | en_US |
dc.identifier.startpage | 1284 | en_US |
dc.identifier.uri | https://doi.org/10.1097/MEG.0000000000002641 | |
dc.identifier.uri | https://hdl.handle.net/20.500.13055/539 | |
dc.identifier.volume | 35 | en_US |
dc.identifier.wos | WOS:001078091300007 | en_US |
dc.identifier.wosquality | Q4 | en_US |
dc.indekslendigikaynak | Web of Science | en_US |
dc.indekslendigikaynak | Scopus | en_US |
dc.indekslendigikaynak | PubMed | en_US |
dc.institutionauthor | Örmeci, Necati | |
dc.language.iso | en | en_US |
dc.publisher | Lippincott Williams & Wilkins | en_US |
dc.relation.ispartof | European Journal of Gastroenterology & Hepatology | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Multicenter Validation | en_US |
dc.subject | FIB-6 | en_US |
dc.subject | MAFLD | en_US |
dc.subject | Biopsy | en_US |
dc.subject | Liver | en_US |
dc.title | Multicenter validation of FIB-6 as a novel machine learning non-invasive score to rule out liver cirrhosis in biopsy-proven MAFLD | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication |
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