J Rheum Dis.  2018 Jan;25(1):3-10. 10.4078/jrd.2018.25.1.3.

Overview of the Process of Conducting Meta-analyses of the Diagnostic Test Accuracy

• Lee YH

• KMID: 2405015
• DOI: http://doi.org/10.4078/jrd.2018.25.1.3

Abstract

Diagnosis is a critical step for clinical treatment. Many individual studies have been conducted to determine the accuracy of various diagnostic tests, but they had small sample sizes and correspondingly inadequate statistical strength. Combining the results from several such studies can help increase the statistical strength and precision of their results. Meta-analysis is a useful tool for evaluating the accuracy of diagnostic tests and can be used to obtain precise estimates when multiple small studies for a given test and subject pool are available. The need for meta-analysis on studies examining diagnostic test accuracy has increased noticeably, and more meta-analyses on diagnostic test accuracy studies are being published. A meta-analysis of diagnostic test accuracy studies differs from a typical meta-analysis because diagnostic test accuracy studies report a pair of statistics, such as sensitivity and specificity, rather than a single statistic. Therefore, meta-analyses of the diagnostic test accuracy need to deal with two summary statistics simultaneously. More complex statistical methods are required for conducting meta-analyses using diagnostic test accuracy studies compared to that required for conventional meta-analysis. This is because the sensitivity and specificity are generally inversely correlated due to a threshold effect, and there is considerable heterogeneity in the results of test accuracy studies. This review provides an overview of the process of meta-analysis of the diagnostic test accuracy.

Keyword

Diagnostic test; Accuracy; Meta-analysis

MeSH Terms

Diagnosis
Diagnostic Tests, Routine*
Population Characteristics
Sample Size
Sensitivity and Specificity

Figure

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  Figure 1. (A) Sensitivity and (B) specificity estimates for ultrasound used for the diagnosis of gout. Circles and lines represent point estimates and 95% confidence intervals (CI), respectively. Circled areas represent relative study sizes. Df: degrees of freedom.

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  Figure 2. Summary receiver-operating characteristic curves for ultrasound for the diagnosis of gout. Solid circles represent the individual studies included in this meta-analysis. The curve shown is a regression line that summarizes the overall diagnostic accuracy. SE (AUC): standard error of the area under the curve, Q*: an index defined by the point on the summary receiver operating characteristic (sROC) curve, where the sensitivity and specificity are equal, SE (Q*): Q* index standard error.

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