Diagnostic test accuracy network meta-analysis methods: A scoping review and empirical assessment
Areti Angeliki Veroniki1, Sofia Tsokani2, Ridhi Agarwal3
1Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, 209 Victoria Street, East Building, Toronto, Ontario M5B 1T8, Canada; Institute of Health Policy Management and Evaluation, University of Toronto, Toronto, Ontario, Canada.
Journal of Clinical Epidemiology
|February 19, 2022
Summary
Diagnostic test accuracy network meta-analysis (DTA-NMA) and meta-regression models are increasingly used. While sensitivity estimates are similar, specificity estimates differ, impacting diagnostic test accuracy network meta-analysis results.
Area of Science:
- Biostatistics
- Medical Informatics
- Health Research Methodology
Background:
- Network meta-analysis (NMA) is a valuable tool for comparing multiple diagnostic tests.
- Diagnostic test accuracy network meta-analysis (DTA-NMA) and hierarchical meta-regression are advanced methods for synthesizing evidence on test accuracy.
- Comparing at least three index tests requires robust statistical approaches.
Purpose of the Study:
- To identify and characterize methodological and application papers on DTA-NMA and hierarchical meta-regression.
- To conduct a descriptive analysis of DTA-NMA and meta-regression application papers.
- To empirically compare DTA-NMA and hierarchical meta-regression methods.
Main Methods:
- Scoping review of major databases up to March 2021.
- Assessment of methodological characteristics of DTA-NMA and meta-regression models.
- Descriptive analysis of application papers and empirical comparison of methods using available data.
Main Results:
- Identified 49 relevant articles, including 9 methodological and 40 application papers.
- Observed a significant increase in DTA-NMA publications in recent years.
- Found comparable sensitivity estimates but higher specificity estimates with meta-regression compared to DTA-NMA.
Conclusions:
- The choice between DTA-NMA and meta-regression depends on data characteristics and software familiarity.
- Methodological choices can influence network meta-analysis results, particularly for specificity.
- Understanding these differences is crucial for accurate diagnostic test evaluation.
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