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An index for diagnostic accuracy in the multiple disease setting
1Department of Biostatistics, University of Pittsburgh, PA 15261-0001, USA.
Rationale And Objectives:
Evaluation of diagnostic accuracy in the clinical environment should entail some assessment of performance in patients with multiple abnormalities. Although receiver operating characteristic (ROC) curves often are used to assess the diagnostic accuracy of imaging systems, the concept is not easily generalizable to patients with multiple abnormalities. I propose a measure of diagnostic accuracy that is a generalization of the area under the ROC curve for a single disease.
Methods:
The proposed measure of diagnostic accuracy is a weighted average of the area under individual ROC curves for the single disease setting and of components representing areas under ROC curves constructed for patients with multiple diseases. Several options are discussed for scoring the presence of abnormality for patients who have two or more abnormalities.
Results:
Methods of estimating diagnostic accuracy are demonstrated on a set of data in which more than one third of the abnormal cases included multiple abnormalities of chest disease.
Conclusion:
An easy-to-use method is given to estimate diagnostic accuracy in the multiple abnormality setting. This should make it easier to incorporate cases with multiple abnormalities when assessing the diagnostic accuracy of imaging systems.