Nonparametric receiver operating characteristic curve analysis with an imperfect gold standard.
Biometrics
; 80(3)2024 Jul 01.
Article
em En
| MEDLINE
| ID: mdl-38994641
ABSTRACT
This article addresses the challenge of estimating receiver operating characteristic (ROC) curves and the areas under these curves (AUC) in the context of an imperfect gold standard, a common issue in diagnostic accuracy studies. We delve into the nonparametric identification and estimation of ROC curves and AUCs when the reference standard for disease status is prone to error. Our approach hinges on the known or estimable accuracy of this imperfect reference standard and the conditional independent assumption, under which we demonstrate the identifiability of ROC curves and propose a nonparametric estimation method. In cases where the accuracy of the imperfect reference standard remains unknown, we establish that while ROC curves are unidentifiable, the sign of the difference between two AUCs is identifiable. This insight leads us to develop a hypothesis-testing method for assessing the relative superiority of AUCs. Compared to the existing methods, the proposed methods are nonparametric so that they do not rely on the parametric model assumptions. In addition, they are applicable to both the ROC/AUC analysis of continuous biomarkers and the AUC analysis of ordinal biomarkers. Our theoretical results and simulation studies validate the proposed methods, which we further illustrate through application in two real-world diagnostic studies.
Palavras-chave
Texto completo:
1
Bases de dados:
MEDLINE
Assunto principal:
Simulação por Computador
/
Curva ROC
/
Área Sob a Curva
Limite:
Humans
Idioma:
En
Revista:
Biometrics
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China