A grey zone for quantitative diagnostic and screening tests.

BACKGROUND Most quantitative tests do not perfectly discriminate between subjects with and without a given disease and their results do not always allow certainty about disease status for diagnostic or screening purposes. We propose a method to construct a three-zone partition for quantitative tests to avoid the binary constraint of a 'black or white' decision that often does not fit the reality of clinical or screening practice. This partition intentionally includes a grey zone between positive and negative conclusions. METHODS AND RESULTS We show that the width of this grey zone depends on the difference between the means of test results for subjects with and without the disease, the variability of the test results and its components (biological, measurement), and the level of the misclassification risks (false positive, false negative) required by the context of use. We illustrate the method by application to the tuberculin skin test and iron deficiency markers in children. CONCLUSION This method can be used both to display the discriminatory performance of a quantitative test in a variety of contexts and to scrutinize its components of variability. Due to the simplicity of the graphical representations, the grey zone approach may be useful during the development of quantitative tests and the publication of their performance.