%0 Journal Article %1 Reitsma2005 %A Reitsma, Johannes B %A Glas, Afina S %A Rutjes, Anne W S %A Scholten, Rob J P M %A Bossuyt, Patrick M %A Zwinderman, Aeilko H %D 2005 %J Journal of clinical epidemiology %K DataInterpretation DiagnosticTechniquesandProcedures Humans Meta-AnalysisasTopic OutcomeAssessment(HealthCare) OutcomeAssessment(HealthCare):methods ROCCurve ReviewLiteratureasTopic SensitivityandSpecificity Statistical %N 10 %P 982-90 %R 10.1016/j.jclinepi.2005.02.022 %T Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. %U http://www.ncbi.nlm.nih.gov/pubmed/16168343 %V 58 %X 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. %@ 0895-4356; 0895-4356

@article{Reitsma2005, abstract = {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.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Reitsma, Johannes B and Glas, Afina S and Rutjes, Anne W S and Scholten, Rob J P M and Bossuyt, Patrick M and Zwinderman, Aeilko H}, biburl = {https://www.bibsonomy.org/bibtex/2435519b677362cadda13723e5ce89c0e/jepcastel}, city = {Department of Clinical Epidemiology and Biostatistics, Academic Medical Center, University of Amsterdam, PO Box 22700, 1100 DE Amsterdam, The Netherlands. j.reitsma@amc.uva.nl}, doi = {10.1016/j.jclinepi.2005.02.022}, interhash = {44379cb48ef38cd0b4ba8638b3356de8}, intrahash = {435519b677362cadda13723e5ce89c0e}, isbn = {0895-4356; 0895-4356}, issn = {0895-4356}, journal = {Journal of clinical epidemiology}, keywords = {DataInterpretation DiagnosticTechniquesandProcedures Humans Meta-AnalysisasTopic OutcomeAssessment(HealthCare) OutcomeAssessment(HealthCare):methods ROCCurve ReviewLiteratureasTopic SensitivityandSpecificity Statistical}, month = {10}, note = {5685<m:linebreak></m:linebreak>LR: 20071115; JID: 8801383; CIN: J Clin Epidemiol. 2006 Dec;59(12):1331-2; author reply 1332-3. PMID: 17098577; RF: 46; 2004/07/26 [received]; 2005/01/10 [revised]; 2005/02/21 [accepted]; ppublish;<m:linebreak></m:linebreak>Proves diagnòstiques}, number = 10, pages = {982-90}, pmid = {16168343}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews.}, url = {http://www.ncbi.nlm.nih.gov/pubmed/16168343}, volume = 58, year = 2005 }