Statistical considerations of length bias for evaluating diagnostic tests in screening studies

Journal of Biometrics & Biostatistics

article

KyungheeK Song¹ 

[1] Division of Biostatistics, Center for Devices and Radiological Health/Food and Drug, Administration

关键词: Length biased sample;    Screening study;    Natural history;    Biological heterogeneity;    Diagnostic test;    Vardi’s bias adjusted nonparametric maximum likelihood estimator;    Linear combination estimator;    Cox estimator;    Empirical distribution function estimator;    Gamma distribution;   

DOI  :  10.4172/2155-6180.S2-001

来源: Hilaris Publisher

【 摘 要 】

A diagnostic test in a screening study detects a clinical condition of interest in its asymptomatic stage. Evaluating the diagnostic test in a screening study is a challenging task since a diagnostic test is evaluated based on its analytical and clinical performance. In order to evaluate clinical performance of a diagnostic test in a screening study, it is crucial to investigate clinical outcome studies such as survival studies. Furthermore, there are important biases to be considered in a screening study. In this paper, statistical issues associated with screening studies are discussed, and statistical adjustment for screening-related bias, which is called length bias, is presented. Both Vardi’s bias-adjusted nonparametric maximum likelihood estimator and linear combination estimators have shown to adjust length bias successfully, and generate bias-adjusted survival curve close to the true survival curve. Finally, some practical issues associated with early detection are also presented.

【 授权许可】

Unknown