Extracting data from diagnostic test accuracy studies for meta-analysis.

Diagnostic test accuracy (DTA) reviews are carried out to summarise and explore the evidence about the accuracy of specific tests.1 Consider a clinical question as an example: What is the diagnostic accuracy of community-based point of care natriuretic peptide testing for chronic heart failure? To answer this question, a DTA review will seek to systematically find and pool individual DTA data in the form of a meta-analysis. However, this can be challenging, particularly when dealing with diagnoses based on measurements with continuous distributions. This is because, typically, individual studies of DTA report the sensitivity and specificity of the test and not the necessary inputs for meta-analysis software, as recommended by the Standards for Reporting Diagnostic Accuracy statement for reporting standards in DTAs.2 The necessary inputs are: Using these four numbers we can generate a 2×2 classification table that compares the test result with the ‘true value’ based on the reference test or ‘gold standard’ (figure 1). Figure 1 Diagnostic accuracy 2×2 classification table, with totals added. FN, false negatives; FP, false positives; TN, true negatives; TP, true positives. To perform meta-analysis, for each study, we need to enter these four numbers into …