A New Diagnostic Accuracy Measure and Cut-Points Selection Criterion

• Activity Number: 500
• Type: Contributed
• Date/Time: Wednesday, August 12, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Medical Devices and Diagnostics
• Author(s): Tuochuan Dong*
• Companies: Novartis
• Keywords: diagnostic test ; measure of diagnostic accuracy ; cut-off selection criterion ; MADET

Abstract

Most diagnostic accuracy measures and criteria for selecting optimal cut-points are only applicable to diseases with binary or three stages. Currently there exist two diagnostic measures for diseases with general k stages: the hypervolume under the manifold (HUM) and the generalized Youden index (GYI). While HUM can not be used for cut-points selection, GYI is only defined upon correct classification rates. This paper proposes a new measure named maximum absolute determinant (MADET) for diseases with k stages (k>=2). This comprehensive new measure utilizes all the available classification information and serves as a cut-points selection criterion as well. Both the geometric and probabilistic interpretations for the new measure are examined. Simulation studies are carried out to investigate its operating characteristics and performance as a measure of diagnostic accuracy as well as cut-points selection criterion. A real data set from Alzheimer's Disease Neuroimaging Initiative (ANDI), is analyzed using the proposed MADET.