Estimation of sensitivity and specificity of diagnostic tests and disease prevalence when the true disease state is unknown

被引:370
作者
Enoe, C [1 ]
Georgiadis, MP
Johnson, WO
机构
[1] Royal Vet & Agr Univ, Dept Anim Sci & Anim Hlth, Div Ethol & Hlth, DK-1870 Frederiksberg C, Denmark
[2] Univ Calif Davis, Sch Vet Med, Dept Med & Epidemiol, Davis, CA 95616 USA
[3] Univ Calif Davis, Div Stat, Davis, CA 95616 USA
关键词
diagnostic tests; sensitivity; specificity; maximum likelihood; Bayesian approach; latent data;
D O I
10.1016/S0167-5877(00)00117-3
中图分类号
S85 [动物医学(兽医学)];
学科分类号
0906 ;
摘要
The performance of a new diagnostic test is frequently evaluated by comparison to a perfect reference test (i.e. a gold standard). In many instances, however, a reference test is less than perfect. In this paper, we review methods for estimation of the accuracy of a diagnostic test when an imperfect reference test with known classification errors is available. Furthermore, we focus our presentation on available methods of estimation of test characteristics when the sensitivity and specificity of both tests are unknown. We present some of the available statistical methods for estimation of the accuracy of diagnostic tests when a reference test does not exist (including maximum likelihood estimation and Bayesian inference). We illustrate the application of the described methods using data from an evaluation of a nested polymerase chain reaction and microscopic examination of kidney imprints for detection of Nucleospora salmonis in rainbow trout. (C) 2000 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:61 / 81
页数:21
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