A1314
Title: Network meta-analysis of diagnostic test accuracy reported at multiple thresholds
Authors: Efthymia Derezea - University of Bristol (United Kingdom) [presenting]
Hayley Jones - University of Bristol (United Kingdom)
Abstract: Network meta-analysis of diagnostic test accuracy (NMA-DTA) is a relatively new field involving combining evidence across studies to evaluate and compare the accuracy of different tests for a given condition. Many commonly used diagnostic tests are continuous biomarkers whose accuracy is evaluated at multiple thresholds within a study. Using current NMA-DTA methods it is feasible to include in an analysis only a few thresholds per study. An approach that can efficiently encompass all available data is discussed. This is a hierarchical model that incorporates multinomial likelihoods for studies reporting results across multiple thresholds and a parametric structure for the relationship between the probability of testing positive and the threshold within each disease class. This approach enables obtaining the accuracy estimates of tests across the whole range of observed thresholds while retaining all the useful properties of standard NMA-DTA methods. Different variations of this model are explored based on the inclusion of study-level random effects and the addition of a further hierarchical structure on the test-level variance components. This method is applied to data from a systematic review of the accuracy of tests for hepatocellular carcinoma in patients with liver cirrhosis.
