TY - JOUR
T1 - Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews
AU - Reitsma, Johannes B.
AU - Glas, Afina S.
AU - Rutjes, Anne W. S.
AU - Scholten, Rob J. P. M.
AU - Bossuyt, Patrick M.
AU - Zwinderman, Aeilko H.
PY - 2005
Y1 - 2005
N2 - Background and Objectives: Studies of diagnostic accuracy most often report pairs of sensitivity and specificity. We demonstrate the advantage of using bivariate meta-regression models to analyze such data. Methods: We discuss the methodology of both the summary Receiver Operating Characteristic (sROC) and the bivariate approach by reanalyzing the data of a published meta-analysis. Results: The sROC approach is the standard method for meta-analyzing diagnostic studies reporting pairs of sensitivity and specificity. This method uses the diagnostic odds ratio as the main outcome measure, which removes the effect of a possible threshold but at the same time loses relevant clinical information about test performance. The bivariate approach preserves the two-dimensional nature of the original data. Pairs of sensitivity and specificity are jointly analyzed, incorporating any correlation that might exist between these two measures using a random effects approach. Explanatory variables can be added to the bivariate model and lead to separate effects on sensitivity and specificity, rather than a net effect on the odds ratio scale as in the sROC approach. The statistical properties of the bivariate model are sound and flexible. Conclusion: The bivariate model can be seen as an improvement and extension of the traditional sROC approach. (c) 2005 Elsevier Inc. All rights reserved
AB - Background and Objectives: Studies of diagnostic accuracy most often report pairs of sensitivity and specificity. We demonstrate the advantage of using bivariate meta-regression models to analyze such data. Methods: We discuss the methodology of both the summary Receiver Operating Characteristic (sROC) and the bivariate approach by reanalyzing the data of a published meta-analysis. Results: The sROC approach is the standard method for meta-analyzing diagnostic studies reporting pairs of sensitivity and specificity. This method uses the diagnostic odds ratio as the main outcome measure, which removes the effect of a possible threshold but at the same time loses relevant clinical information about test performance. The bivariate approach preserves the two-dimensional nature of the original data. Pairs of sensitivity and specificity are jointly analyzed, incorporating any correlation that might exist between these two measures using a random effects approach. Explanatory variables can be added to the bivariate model and lead to separate effects on sensitivity and specificity, rather than a net effect on the odds ratio scale as in the sROC approach. The statistical properties of the bivariate model are sound and flexible. Conclusion: The bivariate model can be seen as an improvement and extension of the traditional sROC approach. (c) 2005 Elsevier Inc. All rights reserved
U2 - https://doi.org/10.1016/j.jclinepi.2005.02.022
DO - https://doi.org/10.1016/j.jclinepi.2005.02.022
M3 - Article
C2 - 16168343
SN - 0895-4356
VL - 58
SP - 982
EP - 990
JO - Journal of Clinical Epidemiology
JF - Journal of Clinical Epidemiology
IS - 10
ER -