25gmds082 10.3205/25gmds082 urn:nbn:de:0183-25gmds0821 Meeting Abstract Weber Weber Philipp P

Institut für Medizinische Biometrie und Epidemiologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany

author Vogel Vogel Frederike F

Institut für Medizinische Biometrie und Epidemiologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany

author Konietschke Konietschke Frank F

Charité - Universitätsmedizin Berlin, Berlin, Germany

author Zapf Zapf Antonia A

Institut für Medizinische Biometrie und Epidemiologie, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany

author German Medical Science GMS Publishing House

Düsseldorf

610 diagnostic accuracy study regression clustered data factorial designs 20251103 engl This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 License. Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). M0631 082 Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie 70. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS) V: Medical Biometry 2: Analysemethoden Jena 20250907 20250911 Abstr. 269 TextIntroduction: The accuracy of diagnostic tests is commonly evaluated by estimating the area under the receiver operating characteristic curve (AUC), as well as sensitivity and specificity at given diagnostic cut-offs.Challenges: However, many diagnostic trials use factorial designs. For example, different combinations of readers and methods may be used to diagnose a patient. Furthermore, diagnostic studies may generate clustered data by repeated measurements over time or several lesions, for example different brain regions. Dependencies between a person's observations must be taken into account in the analysis in order to prevent variance deflation. Lange developed a nonparametric mathematical framework to deal with both of these design aspects, and Lange and Brunner generalized the approach from the AUC to sensitivity and specificity .Additionally, it may be of interest to adjust the estimation procedure of the above mentioned accuracy measures for covariates. For example, it may be the case that age, weight or height influence the diagnostic accuracy of a test. Zapf proposed a nonparametric methodological approach to adjust the AUC for such covariates, while also allowing for factorial designs, but not yet for clustered data.Conclusion: In this talk we present a new, unified method that enables covariate adjustment of the AUC, sensitivity and specificity in studies with factorial designs and clustered data. We will show the properties of the approach using simulated data and illustrate the approach with an example study.The authors declare that they have no competing interests.The authors declare that an ethics committee vote is not required.The contribution has already been published: Lange K 2011 Nichtparametrische analyse diagnostischer Gütemaße bei Clusterdaten [Dissertation] Lange K. Nichtparametrische analyse diagnostischer Gütemaße bei Clusterdaten [Dissertation]. 2011. DOI: 10.53846/goediss-3538 https://doi.org/10.53846/goediss-3538 Zapf A 2009 Multivariates nichtparametrisches Behrens-Fisher-problem MIT Kovariablen [Dissertation] Zapf A. Multivariates nichtparametrisches Behrens-Fisher-problem MIT Kovariablen [Dissertation]. 2009. DOI: 10.53846/goediss-2488 https://doi.org/10.53846/goediss-2488 Lange K Brunner E Sensitivity, specificity and ROC-curves in multiple reader diagnostic trials—a unified, nonparametric approach 2012 Statistical Methodology 490–500 Lange K, Brunner E. Sensitivity, specificity and ROC-curves in multiple reader diagnostic trials—a unified, nonparametric approach. Statistical Methodology. 2012;9(4):490–500. DOI: 10.1016/j.stamet.2011.12.002 http://dx.doi.org/10.1016/j.stamet.2011.12.002 Weber P Kramer K Zapf A Covariate adjustment, factorial designs and clustered data in diagnostic accuracy studies 70th Biometric Colloquium; 2024 Feb 28 – Mar 01; Lübeck, Germany Weber P, Kramer K, Zapf A. Covariate adjustment, factorial designs and clustered data in diagnostic accuracy studies. In: 70th Biometric Colloquium; 2024 Feb 28 – Mar 01; Lübeck, Germany. 0 0 0 0