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Classification of Chronic Kidney Disease Biomarkers to Predict Coronary Artery Calcium

Background/Aims: The link between CKD and CAC has been mostly established by studies of patients who have abnormally high phosphorus levels and advanced CKD or end-stage renal disease. The aim of this study was to examine if there are distinct trajectory classes of serum phosphorus (controlling for eGFR) that are associated CAC in a relatively healthy, community sample. Methods: Phosphorus and eGFR were classified as a combined biomarker variable with 4 trajectory classes by growth mixture modeling. This classification variable was subsequently used to predict CAC as both a binary (i.e., onset) and continuous (i.e., accumulation) outcome using a two-part growth model. Results: Membership in one class of phosphorus trajectory versus the next lowest level was associated with a 97.9 Agatston unit increase in CAC (p <.001). The magnitude of this finding is similar in size as some primary risk factors for cardiovascular disease, including a 55.3 Agatston unit (p <.001) increase associated with age, and a - 75.1 Agatston unit (p <.001) decrease associated with female gender. Conclusions: Classification of phosphorus trajectories provides further definition for prediction of CAC within the conventional ‘normal’ range. Classifying trajectories may help determine clinically-relevant thresholds for interventions aimed at phosphorus reduction.