Meta-Analysis
Copyright ©The Author(s) 2019. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Aug 6, 2019; 7(15): 2022-2037
Published online Aug 6, 2019. doi: 10.12998/wjcc.v7.i15.2022
Performance of common imaging techniques vs serum biomarkers in assessing fibrosis in patients with chronic hepatitis B: A systematic review and meta-analysis
Xue-Ying Xu, Wu-Sheng Wang, Qi-Meng Zhang, Jun-Ling Li, Jin-Bin Sun, Tian-Tian Qin, Hong-Bo Liu
Xue-Ying Xu, Wu-Sheng Wang, Qi-Meng Zhang, Jun-Ling Li, Jin-Bin Sun, Tian-Tian Qin, Hong-Bo Liu, Department of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China
Author contributions: Xu XY, Wang WS, Zhang QM, Li JL, and Liu HB designed the research; Xu XY, Zhang QM, Li JL, Sun JB, and Qin TT performed the research; Sun JB and Qin TT contributed new analytic tools; Xu XY, Wang WS, and Zhang QM analyzed the data; Xu XY, Wang WS, Zhang QM, and Liu HB wrote the paper.
Supported by Social Science Foundation of Liaoning Province, No. L18ATJ001.
Conflict-of-interest statement: The corresponding author attests that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. All authors declare that they have no conflicts of interest.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 checklist, and the manuscript was prepared and revised according to the PRISMA 2009 checklist.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Hong-Bo Liu, PhD, Professor, Research Fellow, Research Scientist, Statistician, Department of Epidemiology and Health Statistics, School of Public Health, China Medical University, No. 77, Puhe Road, Shenyang North New Area, Shenyang 110122, Liaoning Province, China. hbliu@cmu.edu.cn
Received: March 4, 2019
Peer-review started: March 4, 2019
First decision: May 31, 2019
Revised: June 25, 2019
Accepted: July 3, 2019
Article in press: July 3, 2019
Published online: August 6, 2019
Processing time: 156 Days and 23.5 Hours
ARTICLE HIGHLIGHTS
Research background

Liver fibrosis can develop to cirrhosis and even hepatic failure and hepatocellular carcinoma. Approximately one-third of cirrhosis cases worldwide are caused by HBV infection. Therefore, the accurate diagnosis of the extent of liver fibrosis for chronic hepatitis B patients is essential. Many serum biomarkers combining indices/scores and imaging or magnetic resonance imaging techniques have been undergoing dramatic development because of several drawbacks of liver biopsy. These methods have promising results and may improve the management of liver fibrosis. However, most of the previous studies compared the diagnostic effects of these new techniques within the domain of imaging techniques or focused on fibrosis in all chronic liver diseases, which might misestimate the role of these biomarkers. Therefore, we performed a meta-analysis to compare the pooled performance of some common imaging methods with serum biomarkers for prediction of significant fibrosis among HBV-monoinfected patients.

Research motivation

We aimed to assess the accuracy of diagnostic tests for predicting significant fibrosis among patients monoinfected with HBV. Most studies are centered on the domain of imaging techniques and serum biomarkers separately or focused on fibrosis in all chronic liver diseases. Therefore, the key points are that data for HBV infected patients could be extracted independently and we want to integrate and compare the performance of methods of different fields. With the development of medicine and technology, more innovative methods could be invented in the near future. It will provide a boost to precision medicine that chooses a more appropriate and effective method to evaluate liver fibrosis for different populations of patients.

Research objectives

We aimed to compare the pooled performance of some common imaging methods with serum biomarkers for prediction of significant fibrosis among HBV-monoinfected patients. Some serum biomarkers have been calculated and imaging techniques have been developed for the diagnosis of liver fibrosis, respectively. Integrating and comparing the performance of methods of different fields could provide a basis for future research and clinical application and a boost to precision medicine.

Research methods

We examined the areas under the summary receiver operating characteristic curves, the summary diagnostic odds ratios, as well as the summary sensitivities and specificities to further examine the accuracy of all tests for liver fibrosis. Then, we assessed the heterogeneity between studies using the Cochran-Q and I2. And the Deeks funnel plots were used to assess publication bias. Meta-regression was conducted to further accurately explore the covariates that may induce heterogeneity.

Research results

Our meta-analysis revealed that ARFI showed a higher diagnostic accuracy than FibroScan in identifying HBV-related significant fibrosis. Furthermore, it can also be performed in obese patients and in patients with ascites and be integrated in a conventional ultrasound system. MRE, the only MRI index, had the best result in prediction of significant fibrosis. The area under the SROC curve of MRE reaches the standard of “best” and even closes to “1”. The performances of APRI and FIB-4 are poorer than imaging techniques. However, the cut-off value should be considered in future studies.

Research perspectives

Imaging techniques are better than serum biomarkers in prediction of HBV-related liver significant fibrosis in general. MRE is a promising indicator and other serum biomarkers are general.