Background: Newer biomarkers, reflective of biological processes, such as inflammation and fibrosis, cardiac stretch or damage and vascular health may be useful in understanding clinical events in chronic kidney disease (CKD). We assessed whether these newer biomarkers, alone or as a panel, improve risk prediction for renal replacement therapy or death, over and above conventional clinical, demographic and laboratory variables.
Methods: We conducted a prospective observational Canadian cohort study in 2544 CKD patients with estimated glomerular filtration rate (eGFR) of 15-45 mL/min/1.73 m(2), under nephrology care, in urban and rural centers. We measured traditional clinical and laboratory risk factors, as well as newer biomarkers: cystatin C, high sensitivity c-reactive protein (hsCRP), interleukin 6 (IL6), transforming growth factor β1 (TGFβ1), fibroblast growth factor 23 (FGF23), N-terminal probrain natriuretic peptide (NT-proBNP), troponin I and asymmetric dimethylarginine (ADMA). Key outcomes were renal replacement therapy (RRT, dialysis or transplantation) and death, during the first year follow-up after enrollment: a time point important for clinical decision-making for patients and providers.
Results: Newer biomarkers do not improve the prediction of RRT, when added to conventional risk factors such as eGFR, urine albumin to creatinine ratio, hemoglobin, phosphate and albumin. However, in predicting death within 1 year, cystatin C, NT-proBNP, hsCRP and FGF23 values significantly improved model discrimination and reclassification: c statistic increased by absolute 4.3% and Net Reclassification Improvement for categories of low, intermediate and high risk at 11.2%.
Conclusions: Our findings suggest that the addition of newer biomarkers may be useful in predicting death in patients with established CKD within a 1-year timeframe. This information may be useful in informing prognosis and redirect resources to serve patients at higher risk to improve outcomes and sustainability of the nephrology care system.
Keywords: CKD; biomarkers; cohort study; outcomes; prediction.