Statistical methods for the evaluation of diagnostic measurements concerning paired organs

Diagnostic measurements involving paired organs may be modelled using marginal or conditional approaches. Relevant information could be ignored by using marginal models with a mean structure not including information from the fellow organ. The conditional Rosner model can be generalized to a symmetric polychotomous logistic regression model. The rather strong assumptions of the Rosner model are relaxed in this symmetric model. The use of the symmetric model is justified by its relation to discriminant analysis. Additionally, the information of the diagnostic measurements from the fellow organ is taken into account explicitly. Furthermore, in case-control studies this approach corresponds to the sampling scheme. When the status of the fellow organ and the diagnostic measurement of this organ both are available, a surprising effect may be observed; pathological values of the diagnostic measurement from the fellow organ decrease the disease probability of the selected organ. As an example, four different diagnostic procedures from the Erlangen Glaucoma Registry are investigated.