Department of Clinical Epidemiology and Biostatistics
McMaster University
Date :
Wednesday January 23, 2002.
Time :
3:30pm
Address
Burke Science Building
Room:
138
TITLE:
Properties of the Summary ROC Curve in Meta-Analysis
of Diagnostic Test Data
ABSTRACT:
The summary receiver operating characteristic (SROC) curve has been recommended to represent the performance of a diagnostic test, based on data from a meta-analysis. However, little is known about the basic properties of the SROC curve or its estimate. I will discuss how the SROC curve can be characterised in terms of the overall diagnostic odds ratio and the magnitude of inter-study heterogeneity in the odds ratio. The Area Under the Curve (AUC) and an index Q* are proposed as potentially useful summaries of the curve. It is shown that AUC is maximised when the study odds ratios are homogeneous, and that it is quite robust to heterogeneity. An upper bound is derived for AUC based on an exact analytic expression for the homogeneous situation, and a lower bound based on the limit case Q*, defined by the point where sensitivity equals specificity: Q* is invariant to heterogeneity. The standard error of AUC is derived for homogeneous studies, and shown to be a reasonable approximation with heterogeneous studies. The expressions for AUC and its standard error are easily computed in the homogeneous case, and avoid the need for numerical integration in the more general case. SE(AUC) and SE(Q*) are found to be numerically close, with SE(Q*) being larger if the odds ratio is very large.
About the Speaker
Dr. Stephen Walter received his Ph.D. at the University of Edinburgh.
After faculty appointments at the University of Ottawa (1972-75) and Yale
University (1975-82), he joined McMaster University where he is currently
a Professor in the Department of Clinical Epidemiology and Biostatistics.
He has published over 200 refereed journal articles and book chapters on
epidemiology and biostatistical methods. Particular interests include:
disease screening and diagnosis; risk assessment; environmental health;
and analysis of spatial and temporal data patterns. He also collaborates
with clinical colleagues on clinical trials, studies of neurodevelopmental
disorders and physiologic experiments.
References
L. Irwig, P. Macaskill, P. Glasziou and M. Fahey (1995) Meta-Analytic
Methods for Diagnostic Test Accuracy, Journal of
Clinical Epidemiology48, 119-130
S. D. Walter, L. Irwig and P. P. Glasziou (1999) Meta-Analysis of
Diagnostic Tests With Imperfect Reference Standards. Journal of
Clinical Epidemiology52, 943-951.
