Agenda:
An important step before clinical intervention selection is the diagnosis of the condition of a patient. Diagnostic tests are commonly used to confirm or exclude a target condition (e.g. a disease). Decision-making rarely relies on a single diagnostic test accuracy (DTA) study; instead, evidence from multiple DTA studies addressing the same question is used. DTA meta-analysis focuses on evaluating individual tests across separate studies. However, multiple index tests may be available for a target condition, making their comparative accuracy is important for decision-making. Network meta-analysis (NMA) allows for a more integrated and comprehensive evaluation of several diagnostic tests simultaneously in a single model. Over the past few years, several NMA models have been developed to evaluate the comparative accuracy of multiple diagnostic tests. In this Cochrane Learning Live webinar, the presenters will discuss why traditional NMA methods for interventions are unsuitable for DTA studies and highlight basic principles and assumptions of DTA-NMA models, such as handling multiple thresholds. Finally, challenges and opportunities in conducting a DTA-NMA will be explored. The session is of particular interest to review authors who would like to incorporate results from DTA studies comparing multiple diagnostic tests in a review.