For patients with CKD, 10-year atherosclerotic cardiovascular disease (ASCVD) risk prediction models improved risk prediction compared with traditional Pooled Cohort Equations developed for the general population, according to a study published in the Journal of the American Society of Nephrology. Joshua Bundy, PhD, MPH, and colleagues developed and validated 10-year ASCVD risk prediction models for patients with CKD using data from participants with selfreported cardiovascular disease in the Chronic Renal Insufficiency Cohort Study (CRIC). Models were developed using clinically available variables and novel biomarkers. The analyses included 2,604 participants, 252 of whom had incident ASCVD within 10 years of baseline. A model with coefficients estimated within the CRIC sample had higher discrimination than the American College of Cardiology/American Heart Association Pooled Cohort Equations, achieving an area under the receiver operating characteristic curve (AUC) of 0.736. The AUC was 0.760 for the CRIC model developed using clinically available variables. The AUC was 0.771 for the CRIC biomarker-enriched model, which was significantly higher than the clinical model. Compared with the Pooled Cohort Equations, both models improved reclassification of non-events.