Meta-analytic methods for diagnostic test accuracy

Les Irwig*, Petra Macaskill, Paul Glasziou, Michael Fahey

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

393 Citations (Scopus)

Abstract

Meta-analyses of diagnostic test accuracy are uncommon and often based on separate pooling of sensitivity and specificity, which can lead to biased estimates. Recently, several appropriate methods have been developed for meta-analysing diagnostic test data from primary studies. Primary studies usually only provide binary test data, for which Moses et al. have developed a method to estimate Summary Receiver Operating Characteristic Curves, thereby taking account of possible test threshold differences between studies. Several methods are also available for analysing multicategory and continuous test data. The usefulness of applying these methods is constrained by publication bias and the generally poor quality of primary studies of diagnostic test accuracy. Meta-analysts need to highlight important defects in quality and how they affect summary estimates to ensure that better primary studies are available for meta-analysis in the future.

Original languageEnglish
Pages (from-to)119-130
Number of pages12
JournalJournal of Clinical Epidemiology
Volume48
Issue number1
DOIs
Publication statusPublished - Jan 1995
Externally publishedYes

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