Assessment of biopsy-proven liver fibrosis by two-dimensional shear wave elastography: An individual patient data-based meta-analysis

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Abstract

Two-dimensional shear wave elastography (2D-SWE) has proven to be efficient for the evaluation of liver fibrosis in small to moderate-sized clinical trials. We aimed at running a larger-scale meta-analysis of individual data. Centers which have worked with Aixplorer ultrasound equipment were contacted to share their data. Retrospective statistical analysis used direct and paired receiver operating characteristic and area under the receiver operating characteristic curve (AUROC) analyses, accounting for random effects. Data on both 2D-SWE and liver biopsy were available for 1,134 patients from 13 sites, as well as on successful transient elastography in 665 patients. Most patients had chronic hepatitis C (n = 379), hepatitis B (n = 400), or nonalcoholic fatty liver disease (n = 156). AUROCs of 2D-SWE in patients with hepatitis C, hepatitis B, and nonalcoholic fatty liver disease were 86.3%, 90.6%, and 85.5% for diagnosing significant fibrosis and 92.9%, 95.5%, and 91.7% for diagnosing cirrhosis, respectively. The AUROC of 2D-SWE was 0.022-0.084 (95% confidence interval) larger than the AUROC of transient elastography for diagnosing significant fibrosis (P = 0.001) and 0.003-0.034 for diagnosing cirrhosis (P = 0.022) in all patients. This difference was strongest in hepatitis B patients. Conclusion: 2D-SWE has good to excellent performance for the noninvasive staging of liver fibrosis in patients with hepatitis B; further prospective studies are needed for head-to-head comparison between 2D-SWE and other imaging modalities to establish disease-specific appropriate cutoff points for assessment of fibrosis stage. (Hepatology 2018;67:260-272).

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Herrmann, E., de Lédinghen, V., Cassinotto, C., Chu, W. C. W., Leung, V. Y. F., Ferraioli, G., … Friedrich-Rust, M. (2018). Assessment of biopsy-proven liver fibrosis by two-dimensional shear wave elastography: An individual patient data-based meta-analysis. Hepatology, 67(1), 260–272. https://doi.org/10.1002/hep.29179

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