Sensitivity and specificity are likely to be correlated (between studies) because of threshold effects (i.e., because changing the diagnostic threshold affects sensitivity and specificity in opposite directions), necessitating the use of multivariate analytic methods. Meta-analyses of test accuracy present particular challenges compared to reviews of randomized trials of therapeutic interventions, not only because the studies reviewed are exclusively observational, but also because of the inherent associations among the metrics of performance. 3, 4 Meta-analysis of test accuracy can provide an estimate of average test accuracy as well as identify patient-, disease- or test-related modifiers of test performance. The level of test accuracy required for tests to have any impact on clinical outcomes depends on their role (replacement, add-on, or triage test), the setting (screening, diagnosis, prognosis/prediction) of test use, and the specific clinical context. While the diagnostic or predictive accuracy of a medical test does not directly inform on the clinical value of testing, it is a crucial piece of the overall puzzle and one that is essential to synthesize in systematic reviews. Therefore, systematic reviewers are typically faced with the task of putting together the pieces of the puzzle by synthesizing studies that address each component of the framework. 2 Primary studies that directly address all components of the assessment framework are very uncommon. The many existing frameworks for assessing the value of testing propose a stepwise appraisal process, moving from analytic validity (technical test performance), to clinical validity (diagnostic and predictive accuracy), clinical utility (effect on clinical outcomes) and overall cost-effectiveness assessment. Tests affect clinical outcomes indirectly, through the effect of test results on physicians' diagnostic thinking and subsequent management decisions, making it difficult to ascribe patient outcomes to the use of a particular test.

1 Despite their central role in patient care, evaluating the effectiveness of specific tests is challenging.

Diagnostic and predictive tests are an important component of medical care, and clinicians rely on test results to establish diagnosis and guide patient management.

Comprehensive meta analysis accuracy