Target practice: choosing target conditions for test accuracy studies that are relevant to clinical practice

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Please see: Target practice: choosing target conditions for test accuracy studies that are relevant to clinical practice

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S J Lord, research fellow12,
L P Staub, PhD candidate1,
P M M Bossuyt, professor of clinical epidemiology3,
L M Irwig, professor of epidemiology2

¹National Health and Medical Research Council Clinical Trials Centre, University of Sydney, 92-94 Parramatta Road, Locked Bag 77, Camperdown NSW 2050, Australia
²Screening and Test Evaluation Program, School of Public Health, University of Sydney
³Department of Clinical Epidemiology and Biostatistics, Academic Medical Centre, University of Amsterdam, Amsterdam, Netherlands

Correspondence to: S J Lord sally.lord{at}ctc.usyd.edu.au

Accepted 24 March 2011

Clinicians should seek information about how well a new test detects disease that will benefit from clinical intervention rather than simply the presence of any disease

Test accuracy varies depending on how the presence of disease is defined. For example, the sensitivity of computed tomographic (CT) colonography to detect colorectal neoplasia has been estimated at 96% for detecting invasive cancer, 86% for medium to large polyps, but as low as 45% when polyps of all sizes are included in the definition of disease.1 To interpret these results, we need to decide whether all polyps, or what type of polyps, are important to detect.

In this paper, we explain how this principle applies when reading studies of test accuracy. When a disease threshold or set of criteria is available to define a clinically meaningful subset of disease, estimates of test accuracy for detecting the entire spectrum of disease will not apply to this subset. Therefore, clinicians need to look for estimates of test accuracy for detecting classifications of disease that are useful in clinical practice. The clinical value of a test cannot be interpreted from estimates of test accuracy if the disease definition is not clearly stated or if its clinical importance is ambiguous or unknown.

Defining disease for test accuracy studies

The diagnostic accuracy of a test measures how well it distinguishes between the presence and absence of disease. This is traditionally expressed as the sensitivity and specificity of the test. Test sensitivity is the proportion of patients with disease who are correctly identified. Test specificity is the proportion of patients without disease who are correctly identified.

To estimate sensitivity and specificity, accuracy studies require an explicit definition of disease as a dichotomous “present or absent” outcome and a reference standard that can be used to verify the true disease status (box). Typically, the definition …