Asymptotic modeling of electrochemical signaling: Testing Zn in urine for non-invasive bladder cancer diagnosis

Abstract A theoretical model on chemical signaling for diagnosis based on the combination of signals for marker and inert and/or interfering metabolites is described. The model yields asymptotic relationships between the intensities of the signals representative of marker and accompanying metabolites compensating concentration fluctuations. The model fits well with voltammetric features associated to the oxidation of different urine metabolites and Zn(II) reduction in the same urine samples after alkaline digestion. As a result, a non-invasive electrochemical detection of urothelial carcinoma (bladder cancer, BC) is reported. Different diagnostic criteria are described all displaying high sensitivity, specificity and positive/negative predictive values. The described methodology was tested by means of an analytical trial with 46 patients with histological and pathologically confirmed BC, 30 healthy controls and 26 patients diagnosed of other urinary pathologies,