Benish William A
Department of Internal Medicine, Louis Stokes Cleveland VA Medical Center and Case Western Reserve University, Cleveland, OH, USA
Stat Methods Med Res. 2015 Dec;24(6):1044-52. doi: 10.1177/0962280212439742. Epub 2012 Feb 23.
We apply the information theory concept of "channel capacity" to diagnostic test performance and derive an expression for channel capacity in terms of test sensitivity and test specificity. The expected value of the amount of information a diagnostic test will provide is equal to the "mutual information" between the test result and the disease state. For the case in which only two test results and two disease states are considered, mutual information, I(D;R), is a function of sensitivity, specificity, and the pretest probability of disease. The channel capacity of the test is the maximal value of I(D;R) for a given sensitivity and specificity. After deriving an expression for I(D;R) in terms of sensitivity, specificity, and pretest probability, we solve for the value of pretest probability that maximizes I(D;R). Channel capacity is obtained by using this value of pretest probability to calculate I(D;R). Channel capacity provides a convenient and meaningful single parameter measure of diagnostic test performance. It quantifies the upper limit of the amount of information a diagnostic test can be expected to provide about a patient's disease state.
我们将“信道容量”这一信息论概念应用于诊断测试性能，并根据测试灵敏度和测试特异性推导出信道容量的表达式。诊断测试将提供的信息量的期望值等于测试结果与疾病状态之间的“互信息”。对于仅考虑两种测试结果和两种疾病状态的情况，互信息I(D;R)是灵敏度、特异性和疾病预测试概率的函数。测试的信道容量是给定灵敏度和特异性下I(D;R)的最大值。在根据灵敏度、特异性和预测试概率推导出I(D;R)的表达式后，我们求解使I(D;R)最大化的预测试概率值。通过使用此预测试概率值来计算I(D;R)，从而获得信道容量。信道容量为诊断测试性能提供了一种方便且有意义的单参数度量。它量化了诊断测试有望提供的关于患者疾病状态信息量的上限。
