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Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2.

Publication ,  Journal Article
Naringrekar, H; Costa, AF; Lam, E; van der Pol, CB; Bashir, MR; Salameh, J-P; McInnes, MDF
Published in: Can Assoc Radiol J
May 2025

Purpose: Use a tailored version of the Quality Assessment of Diagnostic Accuracy Studies tool to evaluate risk of bias and applicability across LIRADS related publications. Method: A tailored QUADAS-2 tool was created through consensus approach to assess risk of bias and applicability across 37 LI-RADS related publications. Studies were selected from 2017 to 2022 using the assistance of experienced hospital librarians to search for studies evaluating the diagnostic accuracy of CT, MRI, or contrast-enhanced ultrasound for HCC using LI-RADS through multiple different databases. QUADAS-2 assessments were performed in duplicate and independently by 2 authors with experience using the QUADAS-2 tool. Disagreements were resolved with a third expert reviewer. Consensus QUADAS-2 assessments were tabulated for each domain. Results: Using the tailored QUADAS-2 tool, 31 of the 37 included LI-RADS studies were assessed as high risk of bias, and 9 out of 37 studies demonstrated concerns for applicability. Patient selection (21 out of 37 studies) and flow/timing (24 out of 37 studies) domains demonstrated the highest risk of bias. 6 out of 37 studies in the index domain demonstrated high risk of bias. 2 out of 37 studies showed high risk of bias in the reference standard domain. Conclusion: A significant proportion of LI-RADS research is at risk of bias with concerns for applicability. Identifying risk of bias in such research is essential to recognize limitations of a study that may affect the validity of the results. Areas for improvement in LI-RADS research include reducing selection bias, avoiding inappropriate exclusions, and decreasing verification bias.

Duke Scholars

Published In

Can Assoc Radiol J

DOI

EISSN

1488-2361

Publication Date

May 2025

Volume

76

Issue

2

Start / End Page

273 / 286

Location

United States

Related Subject Headings

  • Nuclear Medicine & Medical Imaging
  • Liver Neoplasms
  • Liver
  • Humans
  • Diagnostic Imaging
  • Data Systems
  • Carcinoma, Hepatocellular
  • Bias
  • 3202 Clinical sciences
  • 1103 Clinical Sciences
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Naringrekar, H., Costa, A. F., Lam, E., van der Pol, C. B., Bashir, M. R., Salameh, J.-P., & McInnes, M. D. F. (2025). Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2. Can Assoc Radiol J, 76(2), 273–286. https://doi.org/10.1177/08465371241280874
Naringrekar, Haresh, Andreu F. Costa, Eric Lam, Christian B. van der Pol, Mustafa R. Bashir, Jean-Paul Salameh, and Matthew D. F. McInnes. “Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2.Can Assoc Radiol J 76, no. 2 (May 2025): 273–86. https://doi.org/10.1177/08465371241280874.
Naringrekar H, Costa AF, Lam E, van der Pol CB, Bashir MR, Salameh J-P, et al. Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2. Can Assoc Radiol J. 2025 May;76(2):273–86.
Naringrekar, Haresh, et al. “Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2.Can Assoc Radiol J, vol. 76, no. 2, May 2025, pp. 273–86. Pubmed, doi:10.1177/08465371241280874.
Naringrekar H, Costa AF, Lam E, van der Pol CB, Bashir MR, Salameh J-P, McInnes MDF. Risk of Bias in Liver Imaging Reporting and Data System Studies Using QUADAS-2. Can Assoc Radiol J. 2025 May;76(2):273–286.
Journal cover image

Published In

Can Assoc Radiol J

DOI

EISSN

1488-2361

Publication Date

May 2025

Volume

76

Issue

2

Start / End Page

273 / 286

Location

United States

Related Subject Headings

  • Nuclear Medicine & Medical Imaging
  • Liver Neoplasms
  • Liver
  • Humans
  • Diagnostic Imaging
  • Data Systems
  • Carcinoma, Hepatocellular
  • Bias
  • 3202 Clinical sciences
  • 1103 Clinical Sciences