Salvatore Petta1, Vincent Wai-Sun Wong2,3, Elisabetta Bugianesi4, Anna Ludovica Fracanzani5, Calogero Cammà1, Jean-Baptiste Hiriart6, Grace Lai-Hung Wong2,3, Julien Vergniol6, Anthony Wing-Hung Chan7, Aurora Giannetti1, Wassil Merrouche6, Henry Lik-Yuen Chan2,3, Brigitte Le-Bail7,8, Rosa Lombardi5, Salvatore Guastella1, Antonio Craxì1, Victor de Ledinghen6,9. 1. Sezione di Gastroenterologia, Di.Bi.M.I.S., University of Palermo, Italy. 2. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong. 3. State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong. 4. Division of Gastroenterology, Department of Medical Sciences, University of Torino, Torino, Italy. 5. Department of Pathophysiology and Transplantation, Ca' Granda IRCCS Foundation, Policlinico Hospital, University of Milan, Italy. 6. Centre d'Investigation de la Fibrose hépatique, Hôpital Haut-Lévêque, Bordeaux University Hospital, Pessac, France. 7. Department of Anatomical and Cellular Pathology, The Chinese University of Hong Kong, Hong Kong. 8. INSERM U1053, Bordeaux University, Bordeaux, France. 9. Service de Pathologie, Hôpital Pellegrin, Bordeaux University Hospital, Bordeaux, France.
Abstract
INTRODUCTION: Some evidence suggests an interference of obesity and alanine aminotransferase (ALT) levels on the diagnostic accuracy for advanced fibrosis of noninvasive tools such as liver stiffness measurement (LSM) by FibroScan, Fibrosis-4 (FIB-4), and nonalcoholic fatty liver disease fibrosis score (NFS). We assessed whether the diagnostic accuracy of LSM, Fibrosis-4 (FIB-4), and NFS and strategies based on the combination of these tools is affected by obesity and/or ALT levels. METHODS: We analyzed data from 968 patients with a histological diagnosis of nonalcoholic fatty liver disease. FIB-4, NFS, and LSM by FibroScan were measured. RESULTS: LSM was better than both FIB-4 and NFS for staging F3-F4 fibrosis area under the receiver operating characteristic curve test (AUC) 0.863, 0.777, and 0.765, respectively; P < 0.001 for both), showing higher accuracy and higher negative predictive value (NPV), but lower positive predictive value (PPV). LSM worked less well in high ALT (>100 IU) (AUC 0.811 vs 0.877, P = 0.04; PPV 57.5% vs 62.4%; NPV 90.7% vs 94%) or obese patients (AUC 0.786 vs 0.902, P < 0.001; PPV 58.7% vs 64.8%; NPV 88.3% vs 95.2%), the latter not being affected by the M or XL probe. Consistently, LSM worked better in terms of AUC and accuracy compared with both FIB-4 and NFS only in nonobese or high ALT patients, even with always keeping a slightly lower PPV. A serial combination of FIB-4 or NFS with LSM as the second test in patients in the gray area of the first test retained-in most scenarios-similar PPV and NPV compared with LSM alone. These strategies also increased the diagnostic accuracy of about 20% in all groups of patients, even if with a lower overall accuracy in obese patients (71.3% and 67.1% for FIB-4 and NFS as the first test, respectively) compared to nonobese patients (81.9% and 82.4% for FIB-4 and NFS as the first test, respectively). CONCLUSIONS: All tested noninvasive tools have overall better NPV than PPV. LSM has a better diagnostic accuracy for advanced fibrosis than both FIB-4 and NFS only in nonobese and/or low ALT patients. Serial combination strategies are better than a single tool strategy, regardless of obesity and ALT levels, although the accuracy is lower in obese patients.
INTRODUCTION: Some evidence suggests an interference of obesity and alanine aminotransferase (ALT) levels on the diagnostic accuracy for advanced fibrosis of noninvasive tools such as liver stiffness measurement (LSM) by FibroScan, Fibrosis-4 (FIB-4), and nonalcoholic fatty liver disease fibrosis score (NFS). We assessed whether the diagnostic accuracy of LSM, Fibrosis-4 (FIB-4), and NFS and strategies based on the combination of these tools is affected by obesity and/or ALT levels. METHODS: We analyzed data from 968 patients with a histological diagnosis of nonalcoholic fatty liver disease. FIB-4, NFS, and LSM by FibroScan were measured. RESULTS: LSM was better than both FIB-4 and NFS for staging F3-F4 fibrosis area under the receiver operating characteristic curve test (AUC) 0.863, 0.777, and 0.765, respectively; P < 0.001 for both), showing higher accuracy and higher negative predictive value (NPV), but lower positive predictive value (PPV). LSM worked less well in high ALT (>100 IU) (AUC 0.811 vs 0.877, P = 0.04; PPV 57.5% vs 62.4%; NPV 90.7% vs 94%) or obesepatients (AUC 0.786 vs 0.902, P < 0.001; PPV 58.7% vs 64.8%; NPV 88.3% vs 95.2%), the latter not being affected by the M or XL probe. Consistently, LSM worked better in terms of AUC and accuracy compared with both FIB-4 and NFS only in nonobese or high ALT patients, even with always keeping a slightly lower PPV. A serial combination of FIB-4 or NFS with LSM as the second test in patients in the gray area of the first test retained-in most scenarios-similar PPV and NPV compared with LSM alone. These strategies also increased the diagnostic accuracy of about 20% in all groups of patients, even if with a lower overall accuracy in obesepatients (71.3% and 67.1% for FIB-4 and NFS as the first test, respectively) compared to nonobese patients (81.9% and 82.4% for FIB-4 and NFS as the first test, respectively). CONCLUSIONS: All tested noninvasive tools have overall better NPV than PPV. LSM has a better diagnostic accuracy for advanced fibrosis than both FIB-4 and NFS only in nonobese and/or low ALT patients. Serial combination strategies are better than a single tool strategy, regardless of obesity and ALT levels, although the accuracy is lower in obesepatients.
Authors: Fasiha Kanwal; Jay H Shubrook; Leon A Adams; Kim Pfotenhauer; Vincent Wai-Sun Wong; Eugene Wright; Manal F Abdelmalek; Stephen A Harrison; Rohit Loomba; Christos S Mantzoros; Elisabetta Bugianesi; Robert H Eckel; Lee M Kaplan; Hashem B El-Serag; Kenneth Cusi Journal: Gastroenterology Date: 2021-09-20 Impact factor: 33.883
Authors: Ferenc Emil Mózes; Jenny A Lee; Emmanuel Anandraj Selvaraj; Arjun Narayan Ajmer Jayaswal; Michael Trauner; Jerome Boursier; Céline Fournier; Katharina Staufer; Rudolf E Stauber; Elisabetta Bugianesi; Ramy Younes; Silvia Gaia; Monica Lupșor-Platon; Salvatore Petta; Toshihide Shima; Takeshi Okanoue; Sanjiv Mahadeva; Wah-Kheong Chan; Peter J Eddowes; Gideon M Hirschfield; Philip Noel Newsome; Vincent Wai-Sun Wong; Victor de Ledinghen; Jiangao Fan; Feng Shen; Jeremy F Cobbold; Yoshio Sumida; Akira Okajima; Jörn M Schattenberg; Christian Labenz; Won Kim; Myoung Seok Lee; Johannes Wiegand; Thomas Karlas; Yusuf Yılmaz; Guruprasad Padur Aithal; Naaventhan Palaniyappan; Christophe Cassinotto; Sandeep Aggarwal; Harshit Garg; Geraldine J Ooi; Atsushi Nakajima; Masato Yoneda; Marianne Ziol; Nathalie Barget; Andreas Geier; Theresa Tuthill; M Julia Brosnan; Quentin Mark Anstee; Stefan Neubauer; Stephen A Harrison; Patrick M Bossuyt; Michael Pavlides Journal: Gut Date: 2021-05-17 Impact factor: 23.059