Evaluation of diagnostic tests without gold standards

This paper reviews statistical methods developed to estimate the sensitivity and specificity of screening or diagnostic tests when the fallible tests are not evaluated against a gold standard. It gives a brief summary of the earlier historical developments and focuses on the more recent methods. It covers Bayesian approaches and longitudinal studies with repeated testing. In particular, it reviews the procedures that do not require the assumption of independence between tests conditional on the true disease status.

[1]  J. Neyman,et al.  Outline of statistical treatment of the problem of diagnosis. , 1947, Public health reports.

[2]  N. Mantel Evaluation of a Class of Diagnostic Tests , 1951 .

[3]  J. Gart,et al.  Comparison of a screening test and a reference test in epidemiologic studies. II. A probabilistic model for the comparison of diagnostic tests. , 1966, American journal of epidemiology.

[4]  L. A. Goodman Exploratory latent structure analysis using both identifiable and unidentifiable models , 1974 .

[5]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[6]  J. Wittes,et al.  The estimation of false negatives in medical screening. , 1978, Biometrics.

[7]  A. P. Dawid,et al.  Maximum Likelihood Estimation of Observer Error‐Rates Using the EM Algorithm , 1979 .

[8]  S. Walter,et al.  Estimating the error rates of diagnostic tests. , 1980, Biometrics.

[9]  L. A. Thibodeaul Evaluating Diagnostic Tests , 1981 .

[10]  M Staquet,et al.  Methodology for the assessment of new dichotomous diagnostic tests. , 1981, Journal of chronic diseases.

[11]  M A Young,et al.  Evaluating diagnostic criteria: a latent class paradigm. , 1982, Journal of psychiatric research.

[12]  B C Gladen,et al.  Estimating disease rates from a diagnostic test. , 1984, American journal of epidemiology.

[13]  L. A. Goodman,et al.  Latent Structure Analysis of a Set of Multidimensional Contingency Tables , 1984 .

[14]  P M Vacek,et al.  The effect of conditional dependence on the evaluation of diagnostic tests. , 1985, Biometrics.

[15]  D. Rindskopf,et al.  The value of latent class analysis in medical diagnosis. , 1986, Statistics in medicine.

[16]  W. Blattner,et al.  A method for predicting individual HIV infection status in the absence of clinical information. , 1988, AIDS research and human retroviruses.

[17]  M A Espeland,et al.  Assessing diagnostic reliability and estimating incidence rates associated with a strictly progressive disease: dental caries. , 1988, Statistics in medicine.

[18]  S D Walter,et al.  Estimation of test error rates, disease prevalence and relative risk from misclassified data: a review. , 1988, Journal of clinical epidemiology.

[19]  N. Nagelkerke,et al.  Instrumental variables in the evaluation of diagnostic test procedures when the true disease state is unknown. , 1988, Statistics in medicine.

[20]  M. Espeland,et al.  Using latent class models to characterize and assess relative error in discrete measurements. , 1989, Biometrics.

[21]  Mark A. Espeland,et al.  Joint Estimation of Incidence and Diagnostic Error Rates from Irregular Longitudinal Data , 1989 .

[22]  P N Valenstein,et al.  Evaluating diagnostic tests with imperfect standards. , 1990, American journal of clinical pathology.

[23]  Stuart G. Baker,et al.  Evaluating a new test using a reference test with estimated sensitivity and specificity , 1991 .

[24]  D. Spiegelhalter,et al.  Modelling Complexity: Applications of Gibbs Sampling in Medicine , 1993 .

[25]  V. De Gruttola,et al.  Modelling progression of CD4-lymphocyte count and its relationship to survival time. , 1994, Biometrics.

[26]  A. Formann,et al.  Measurement errors in caries diagnosis: some further latent class models. , 1994, Biometrics.

[27]  M. Becker,et al.  ANALYSIS OF CROSS- CLASSIFICATIONS OF COUNTS USING MODELS FOR MARGINAL DISTRIBUTIONS: AN APPLICATION TO TRENDS IN ATTITUDES ON LEGALIZED ABORTION , 1994 .

[28]  A. Agresti,et al.  Simultaneously Modeling Joint and Marginal Distributions of Multivariate Categorical Responses , 1994 .

[29]  M. Wulfsohn,et al.  Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS , 1995 .

[30]  S G Baker,et al.  Evaluating multiple diagnostic tests with partial verification. , 1995, Biometrics.

[31]  L. Joseph,et al.  Bayesian estimation of disease prevalence and the parameters of diagnostic tests in the absence of a gold standard. , 1995, American journal of epidemiology.

[32]  M. Tan,et al.  Random effects models in latent class analysis for evaluating accuracy of diagnostic tests. , 1996, Biometrics.

[33]  I Yang,et al.  Latent variable modeling of diagnostic accuracy. , 1997, Biometrics.

[34]  X H Zhou,et al.  Correcting for verification bias in studies of a diagnostic test's accuracy , 1998, Statistical methods in medical research.