A non-inferiority test for diagnostic accuracy based on the paired partial areas under ROC curves

被引:41
作者
Li, Chi-Rong [1 ,2 ]
Liao, Chen-Tuo [1 ]
Liu, Jen-Pei [1 ,3 ]
机构
[1] Natl Taiwan Univ, Inst Agron, Div Biometry, Taipei 10764, Taiwan
[2] Natl Taiwan Univ, Coll Bioresources & Agr, Consulting Ctr Stat & Bioinformat, Taipei 10764, Taiwan
[3] Natl Hlth Res Inst, Div Biostat & Bioinformat, Zhunan, Taiwan
关键词
sensitivity; specificity; generalized p-value; generalized confidence interval; non-parametric method; maximum likelihood method;
D O I
10.1002/sim.3121
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Non-inferiority is a reasonable approach to assessing the diagnostic accuracy of a new diagnostic test if it provides an easier administration or reduces the cost. The area under the receiver operating characteristic (ROC) curve is one of the common measures for the overall diagnostic accuracy. However, it may not differentiate the various shapes of the ROC curves with different diagnostic significances. The partial area under the ROC curve (PAUROC) may present an alternative that can provide additional and complimentary information for some diagnostic tests which require false-positive rate that does not exceed a certain level. Non-parametric and maximum likelihood methods can be used for the non-inferiority tests based on the difference in paired PAUROCs. However, their performance has not been investigated in finite samples. We propose to use the concept of generalized p-value to construct a non-inferiority test for diagnostic accuracy based on the difference in paired PAUROCs. Simulation results show that the proposed non-inferiority test not only adequately controls the size at the nominal level but also is uniformly more powerful than the non-parametric methods. The proposed method is illustrated with a numerical example using published data. Copyright (C) 2007 John Wiley & Sons, Ltd.
引用
收藏
页码:1762 / 1776
页数:15
相关论文
共 36 条
[1]  
Aoki K, 1997, J Epidemiol, V7, P143
[2]   A proposed design and analysis for comparing digital and analog mammography: Special receiver operating characteristic methods for cancer screening [J].
Baker, SG ;
Pinsky, PF .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2001, 96 (454) :421-428
[3]   Identifying combinations of cancer markers for further study as triggers of early intervention [J].
Baker, SG .
BIOMETRICS, 2000, 56 (04) :1082-1087
[4]   Evaluation of proscriptive health care policy implementation in screening mammography [J].
Beam, CA ;
Conant, EF ;
Sickles, EA ;
Weinstein, SP .
RADIOLOGY, 2003, 229 (02) :534-540
[5]   MULTI-PARAMETER HYPOTHESIS-TESTING AND ACCEPTANCE SAMPLING [J].
BERGER, RL .
TECHNOMETRICS, 1982, 24 (04) :295-300
[6]   AN ANALYSIS OF TRANSFORMATIONS [J].
BOX, GEP ;
COX, DR .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1964, 26 (02) :211-252
[7]   COMPARING THE AREAS UNDER 2 OR MORE CORRELATED RECEIVER OPERATING CHARACTERISTIC CURVES - A NONPARAMETRIC APPROACH [J].
DELONG, ER ;
DELONG, DM ;
CLARKEPEARSON, DI .
BIOMETRICS, 1988, 44 (03) :837-845
[8]   Partial AUC estimation and regression [J].
Dodd, LE ;
Pepe, MS .
BIOMETRICS, 2003, 59 (03) :614-623
[9]  
*FDA, 2006, IN PRESS IN VITR DIA
[10]  
FEINSTEIN A, 2001, PRINCIPLE MED STAT, P455