Diagnostic test accuracy network meta-analysis methods: A scoping review and empirical assessment

Date & Time
Wednesday, September 6, 2023, 2:45 PM - 2:55 PM
Location Name
Session Type
Oral presentation
Screening and diagnostic test accuracy synthesis methods
Oral session
Diagnostic Test Accuracy and prognostic evidence
Tsokani S1, Veroniki AA2, Agarwal R3, Pagkalidou E4, Rücker G5, Mavridis D6, Takwoingi Y7
1Department of Primary Education, School of Education, University of Ioannina, Greece; Methods Support Unit, Cochrane Central Executive Team, UK
2University of Toronto; St. Michael’s Hospital, Unity Health Toronto, Canada
3Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, UK
4Department of Hygiene, Social-Preventive Medicine and Medical Statistics, Medical School, Aristotle University of Thessaloniki, Greece
5Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Germany
6Department of Primary Education, School of Education, University of Ioannina, Greece
7Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham; NIHR Birmingham Biomedical Research Centre, University Hospitals Birmingham NHS Foundation Trust and University of Birmingham, UK

Background: The first and crucial step in the intervention selection process is the diagnosis of the patient’s condition. In healthcare settings, diagnostic tests are commonly used to confirm or exclude a target condition (disease). Most diagnostic test accuracy (DTA) meta-analyses evaluate the accuracy of a single index test at a time; however, there may be several index tests available for a target condition. Comparative accuracy of index tests for a certain target condition is important for decision-making. To compare the accuracy of multiple index tests, several comparative meta-analysis models have been developed over the past few years.
Objectives: To present and discuss methods that have been recognized in our recent scoping review for comparing at least three index tests coming from a variety of studies within a single framework.
Methods: We conducted a scoping review up until March 3, 2021, to identify methodological and application papers reporting a model developed specifically for diagnostic test accuracy network meta-analysis (DTA-NMA) or a hierarchical meta-regression method for comparing at least three index tests. We reviewed and summarized the characteristics of the collected methods and the application papers and compared DTA-NMA and hierarchical meta-regression methods empirically, using the collected application papers.
Results: Publications of comparative meta-analyses with three or more index tests have increased steeply over the past few years. Our research resulted in 49 articles plus 1 companion report: 9 methodological (describing 11 different DTA-NMA models) and 40 application papers of DTA-NMAs or meta-regression. Most of the application papers employed a meta-regression model. In the empirical assessment, meta-regression produced on average higher estimates of specificity than DTA-NMA models while sensitivity estimates were comparable.
Conclusions: DTA-NMA models may yield different results. The inclusion of different thresholds for test positivity, design differences, and software familiarity will determine which DTA-NMA model is appropriate.
Patient, public and/or healthcare consumer involvement: With a good and accurate diagnosis, patients have the best chance of achieving a positive health outcome based on clinical decisions made after understanding their health issue correctly.