Document Type
Article
Publication Date
10-27-2022
Abstract
Background: The purpose of this systematic literature review (SLR) was to evaluate the accuracy of noninvasive diagnostic tools in detecting significant or advanced (F2/F3) fibrosis among patients with nonalcoholic fatty liver (NAFL) in the US healthcare context.
Methods: The SLR was conducted in PubMed and Web of Science, with an additional hand search of public domains and citations, in line with the PRISMA statement. The study included US-based original research on diagnostic test sensitivity, specificity and accuracy.
Results: Twenty studies were included in qualitative evidence synthesis. Imaging techniques with the highest diagnostic accuracy in F2/F3 detection and differentiation were magnetic resonance elastography and vibration-controlled transient elastography. The most promising standard blood biomarkers were NAFLD fibrosis score and FIB-4. The novel diagnostic tools showed good overall accuracy, particularly a score composed of body mass index, GGT, 25-OH-vitamin D, and platelet count. The novel approaches in liver fibrosis detection successfully combine imaging techniques and blood biomarkers.
Conclusions: While noninvasive techniques could overcome some limitations of liver biopsy, a tool that would provide a sufficiently sensitive and reliable estimate of changes in fibrosis development and regression is still missing.
Recommended Citation
Gosalia, Dhaval; Ratziu, Vlad; Stanicic, Filip; Vukicevic, Djurdja; Zah, Vladimir; Gunn, Nadege; Halegoua-De Marzio, Dina; and Tran, Tram, "Accuracy of Noninvasive Diagnostic Tests for the Detection of Significant and Advanced Fibrosis Stages in Nonalcoholic Fatty Liver Disease: A Systematic Literature Review of the US Studies" (2022). Department of Medicine Faculty Papers. Paper 393.
https://jdc.jefferson.edu/medfp/393
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Language
English
Comments
This is the author's final published version in Diagnostics, Volume 12, Issue 11, November 2022, Article number 2608.
The final published version is available at https://doi.org/10.3390/diagnostics12112608. Copyright © 2022 by the authors. Licensee MDPI, Basel, Switzerland.