QUADAS-C: A Tool for Assessing Risk of Bias in Comparative Diagnostic Accuracy Studies

Abstract

Comparative diagnostic test accuracy studies assess and compare the accuracy of two or more tests in the same study. While these studies have the potential to yield reliable evidence regarding comparative accuracy, shortcomings in the design, conduct, and analysis may bias their results. The currently recommended quality assessment tool for diagnostic test accuracy studies, QUADAS-2, is not designed for the assessment of test comparisons.We developed QUADAS-C as an extension to QUADAS-2 to assess the risk of bias in comparative diagnostic test accuracy studies. Through a four-round Delphi study involving 24 international experts in test evaluation and a face-to-face consensus meeting, we developed an initial version of the tool which was revised and finalized following a pilot study among potential users.QUADAS-C retains the same four-domain structure of QUADAS-2 (Patient Selection, Index Test, Reference Standard, and Flow and Timing) and is comprised of additional questions to each QUADAS-2 domain. A risk of bias judgment for comparative accuracy requires a risk of bias judgment for the accuracy of each test (resulting from QUADAS-2) and additional criteria specific to test comparisons. Examples of such additional criteria include whether participants either received all index tests or were randomized to index tests, and whether index tests were interpreted blind to the results of other index tests.QUADAS-C will be useful for systematic reviews of diagnostic test accuracy addressing comparative questions. Furthermore, researchers may use this tool to identify and avoid risk of bias when designing a comparative diagnostic test accuracy study.

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis

“…This guideline includes four domains (patient selection, index test, reference standard, flow, and timing) in the risk of bias and three domains (patient selection, index test, reference standard) in applicability concerns. This new tool is an AI-specific extension to QUADAS-2 28 and QUADAS-C, 29 providing researchers with a specific framework to evaluate the risk of bias and applicability when conducting reviews that evaluate AI-centered diagnostic test accuracy. Conflicts were discussed with a third collaborator (F-HL).…”

MRI detection of suspected nasopharyngeal carcinoma: a systematic review and meta-analysis

“…Potential study bias was assessed using the QUADAS-2 metric [ 24 , 36 ]. Three studies were deemed at risk of selection bias due to case–control design [ 33 ], limited description of inclusion [ 31 ] or exclusion [ 35 ] criteria.…”

Health Technology Assessment of Diagnostic Tests: A state of the art review of methods guidance from international organisations

“…We also noted absence of advice on how to evaluate non–inferiority, with no guidance on how to identify, summarise and interpret comparative accuracy studies, which should be the ideal studies to assess non-inferiority [33]. A new tool, QUADAS-C, has recently been developed to specifically address risk of bias in comparative accuracy studies [34], and may be helpful in future guidance and updates. In addition, we would question whether sufficient attention has so far been paid to the complexities of identifying and interpreting direct evidence, and how a judgement is made that this evidence is sufficient or insufficient for decision–making.…”