Analytical validation of a multi-biomarker algorithmic test for prediction of progressive kidney function decline in patients with early-stage kidney disease.

Background: The KidneyIntelX™ test applies a machine learning algorithm that incorporates plasma biomarkers and clinical variables to produce a composite risk score to predict a progressive decline in kidney function in patients with type 2 diabetes (T2D) and early-stage chronic kidney disease (CKD). The following studies describe the analytical validation of the KidneyIntelX assay including impact of observed methodologic variability on the composite risk score.

Methods: Analytical performance studies of sensitivity, precision, and linearity were performed on three biomarkers assayed in multiplexed format: kidney injury molecule-1 (KIM-1), soluble tumor necrosis factor receptor-1 (sTNFR-1) and soluble tumor necrosis factor receptor-2 (sTNFR-2) based on Clinical Laboratory Standards Institute (CLSI) guidelines.