AIM: To assess the performance of several non-invasive markers and of our recently proposed stepwise combination algorithms to diagnose significant fibrosis (F > or = 2 by METAVIR) and cirrhosis (F4 by METAVIR) in chronic hepatitis B (CHB). METHODS: One hundred and ten consecutive patients (80 males, 30 females, mean age: 42.6 +/- 11.3) with CHB undergoing diagnostic liver biopsy were included. AST-to-Platelet ratio (APRI), Fornso index, AST-to-ALT Ratio, Goteborg University Cirrhosis Index (GUCI), Hui's model and Fibrotest were measured on the day of liver biopsy. The performance of these methods and of sequential algorithms combining Fibrotest, APRI and biopsy was defined by positive (PPV) and negative (NPV) predictive values, accuracy and area under the curve (AUC). RESULTS: PPV for significant fibrosis was excellent (100%) with Forns and high (> 92%) with APRI, GUCI, Fibrotest and Hui. However, significant fibrosis could not be excluded by any marker (NPV < 65%). Fibrotest had the best PPV and NPV for cirrhosis (87% and 90%, respectively). Fibrotest showed the best AUC for both significant fibrosis and cirrhosis (0.85 and 0.76, respectively). Stepwise combination algorithms of APRI, Fibrotest and biopsy showed excellent performance (0.96 AUC, 100% NPV) for significant fibrosis and 0.95 AUC, 98% NPV for cirrhosis, with 50%-80% reduced need for liver biopsy. CONCLUSION: In CHB sequential combination of APRI, Fibrotest and liver biopsy greatly improves the diagnostic performance of the single non-invasive markers. Need for liver biopsy is reduced by 50%-80% but cannot be completely avoided. Non-invasive markers and biopsy should be considered as agonists and not antagonists towards the common goal of estimating liver fibrosis.
AIM: To assess the performance of several non-invasive markers and of our recently proposed stepwise combination algorithms to diagnose significant fibrosis (F > or = 2 by METAVIR) and cirrhosis (F4 by METAVIR) in chronic hepatitis B (CHB). METHODS: One hundred and ten consecutive patients (80 males, 30 females, mean age: 42.6 +/- 11.3) with CHB undergoing diagnostic liver biopsy were included. AST-to-Platelet ratio (APRI), Fornso index, AST-to-ALT Ratio, Goteborg University Cirrhosis Index (GUCI), Hui's model and Fibrotest were measured on the day of liver biopsy. The performance of these methods and of sequential algorithms combining Fibrotest, APRI and biopsy was defined by positive (PPV) and negative (NPV) predictive values, accuracy and area under the curve (AUC). RESULTS: PPV for significant fibrosis was excellent (100%) with Forns and high (> 92%) with APRI, GUCI, Fibrotest and Hui. However, significant fibrosis could not be excluded by any marker (NPV < 65%). Fibrotest had the best PPV and NPV for cirrhosis (87% and 90%, respectively). Fibrotest showed the best AUC for both significant fibrosis and cirrhosis (0.85 and 0.76, respectively). Stepwise combination algorithms of APRI, Fibrotest and biopsy showed excellent performance (0.96 AUC, 100% NPV) for significant fibrosis and 0.95 AUC, 98% NPV for cirrhosis, with 50%-80% reduced need for liver biopsy. CONCLUSION: In CHB sequential combination of APRI, Fibrotest and liver biopsy greatly improves the diagnostic performance of the single non-invasive markers. Need for liver biopsy is reduced by 50%-80% but cannot be completely avoided. Non-invasive markers and biopsy should be considered as agonists and not antagonists towards the common goal of estimating liver fibrosis.
Authors: Xavier Forns; Sergi Ampurdanès; Josep M Llovet; John Aponte; Llorenç Quintó; Eva Martínez-Bauer; Miquel Bruguera; Jose Maria Sánchez-Tapias; Juan Rodés Journal: Hepatology Date: 2002-10 Impact factor: 17.425
Authors: Chun-Tao Wai; Joel K Greenson; Robert J Fontana; John D Kalbfleisch; Jorge A Marrero; Hari S Conjeevaram; Anna S-F Lok Journal: Hepatology Date: 2003-08 Impact factor: 17.425
Authors: Timothy J Gunneson; K V Narayanan Menon; Russell H Wiesner; Judith A Daniels; J Eileen Hay; Michael R Charlton; David J Brandhagen; Charles B Rosen; Michael K Porayko Journal: Am J Gastroenterol Date: 2002-06 Impact factor: 10.864
Authors: J Á Cuenca-Gómez; J Salas-Coronas; A B Lozano-Serrano; J Vázquez-Villegas; M J Soriano-Pérez; M Estévez-Escobar; A Villarejo-Ordóñez; M T Cabezas-Fernández Journal: Eur J Clin Microbiol Infect Dis Date: 2016-06-07 Impact factor: 3.267
Authors: John R Petersen; Heather L Stevenson; Krishna S Kasturi; Ashutosh Naniwadekar; Julie Parkes; Richard Cross; William M Rosenberg; Shu-Yuan Xiao; Ned Snyder Journal: J Clin Gastroenterol Date: 2014-04 Impact factor: 3.062