Sequential evaluation of a medical diagnostic test with binary outcomes.
In a study evaluating a medical diagnostic test, human samples are valuable and often costly, therefore prime concerns require termination of the study if the test is evidently inefficient (or efficient) in diagnosis of diseases in order to keep the number of samples as low as possible. In this paper, we propose sequential designs to evaluate the sensitivity and specificity of a diagnostic test. One method allows early stopping if the sensitivity and specificity of a new medical test are both within the level of tolerance. Another method terminates the study if either the sensitivity or the specificity is below the minimally acceptable level. The latter method minimizes the expected sample size when the test does not meet expectations on performance, and illustrates substantial advantage of having smaller expected sample sizes in various two-stage designs compared to the sample sizes of single-stage designs when a diagnostic test is not promising.
Shu
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Biostatistics Program and Department of Statistics, George Washington University, 2140 Pennsylvania Ave. NW, Washington, DC 20037, USA.
Liu
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Li
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D003955:Diagnostic Tests, Routine / Q000379:methods / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D017063:Outcome Assessment, Health Care; D018401:Sample Size; D012680:Sensitivity and Specificity