Performance of a multi-biomarker panel for prediction of cardiovascular event in patients with chronic kidney disease

Abstract

BackgroundPatients with chronic kidney disease (CKD) undergoing coronary catheterization are at increased risk of cardiovascular events (CVE). Measuring biomarkers before the procedure may guide clinicians in identifying patients at higher risk of future cardiovascular events. MethodsIn this sub-study the Catheter Sampled Blood Archive in Cardiovascular Diseases (CASABLANCA), 927 patients underwent coronary catheterization and were followed up for two years. Using machine learning algorithm and targeted proteomics from samples of patients with CKD, 4 biomarkers (kidney injury molecule-1, N-terminal pro B-type natriuretic peptide, osteopontin, and tissue inhibitor of metalloproteinase-1) were integrated into a prognostic algorithm to predict CVE. Results from the panel are expressed in a graded fashion (CVE higher risk and lower risk) using a data-driven cutoff optimized for balanced sensitivity and specificity. ResultsDuring the 2-year follow-up, 74 CVE were ascertained. 51 (rate: 51/378 = 13.5%) events occurred in stage 1–2 CKD and 23 (rate: 23/68 = 33.8%) events occurred in stage 3–5 CKD. The C-statistic for predicting 2-years cardiovascular events in all 446 patients was 0.77 (0.72, 0.82). The model was well-calibrated (Hosmer-Lemeshow test p-value >0.40). Considering patients at CVE lower-risk within each CKD staging group as a reference, the hazard ratio (95% confidence interval) of cardiovascular events was 2.82 (1.53, 5.22) for CKD stage 1–2/CVE higher-risk, and 8.32 (1.12, 61.76) for CKD stage 3–5/CVE higher-risk. ConclusionMeasuring biomarker panel prior to coronary catheterization may be useful to individualize CVE risk assessment among patients with CKD.