Verification Bias. An Under-Recognized Source of Error in Assessing the Efficacy of MRI of the Meniscii.

Michael L. Richardson, Jonelle M. Petscavage

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Rationale and Objectives: The sensitivity and specificity of magnetic resonance imaging (MRI) for diagnosis of meniscal tears has been studied extensively, with tears usually verified by surgery. However, surgically unverified cases are often not considered in these studies, leading to verification bias, which can falsely increase the sensitivity and decrease the specificity estimates. Our study suggests that such bias may be very common in the meniscal MRI literature, and illustrates techniques to detect and correct for such bias. Materials and Methods: PubMed was searched for articles estimating sensitivity and specificity of MRI for meniscal tears. These were assessed for verification bias, deemed potentially present if a study included any patients whose MRI findings were not surgically verified. Retrospective global sensitivity analysis (GSA) was performed when possible. Results: Thirty-nine of the 314 studies retrieved from PubMed specifically dealt with meniscal tears. All 39 included unverified patients, and hence, potential verification bias. Only seven articles included sufficient information to perform GSA. Of these, one showed definite verification bias, two showed no bias, and four others showed bias within certain ranges of disease prevalence. Only 9 of 39 acknowledged the possibility of verification bias. Conclusion: Verification bias is underrecognized and potentially common in published estimates of the sensitivity and specificity of MRI for the diagnosis of meniscal tears. When possible, it should be avoided by proper study design. If unavoidable, it should be acknowledged. Investigators should tabulate unverified as well as verified data. Finally, verification bias should be estimated; if present, corrected estimates of sensitivity and specificity should be used. Our online web-based calculator makes this process relatively easy.

Original languageEnglish (US)
Pages (from-to)1376-1381
Number of pages6
JournalAcademic Radiology
Volume18
Issue number11
DOIs
StatePublished - Nov 2011

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging

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