Abstract 15670: Age-related Differences in the Contribution of Systolic Blood Pressure and Biomarkers to Cardiovascular Disease Risk Prediction: The Atherosclerosis Risk in Communities (ARIC) Study

Abstract

I ntroduction: Systolic blood pressure (SBP) is an important component of all cardiovascular disease (CVD) risk prediction equations but its biological variability and impact on estimated risk is a concern. Furthermore, predictive value of SBP may differ in older individuals where traditional risk factors (TRF) are less predictive. Hypothesis: Biomarkers reflecting hypertension-related end organ injury (hsTnT, NT-proBNP, eGFR), improve CVD risk prediction in older but not middle age adults as compared to SBP. Methods: Using data from visits 2 (1990-92) and 5 (2011-13) of ARIC, we developed 3 models- Model 1 included all TRF; Model 2- all TRF except SBP + individual biomarkers and Model 3 all TRF + individual biomarkers. C-statistics were used to assess risk discrimination for coronary heart disease, stroke, heart failure, and CVD. Results: After excluding those with prevalent CVD, there were 12,567 individuals at visit 2 (mean age 57, SD 6 years; 43% men) and 4,508 individuals at visit 5 (mean age 76, SD 5 years; 37% men). Over a median (IQR) follow-up time of 22 (12.4–26.7) years and 6.2 (5.4–6.8) years, the incidence rates of CVD events (per 1000 person-years) were 19.0 and 21.8 at visits 2 and 5, respectively. At visit 2, the model with SBP and biomarkers resulted in the largest improvement in C-statistic and SBP contributed to all models. However, at visit 5, removing SBP from the models with the biomarkers had no impact on C-statistic while the addition of the biomarkers (especially hsTnT and NT-proBNP) significantly improved C-statistics for most outcomes ( Table ). Among the biomarkers eGFR had the least additive value. Conclusions: HsTnT and NT-proBNP significantly improve risk discrimination of CHD, stroke, and HF among middle and older adults, while SBP has value in middle age but not in older age. Biomarkers should be considered in risk prediction equations in older individuals where the value of TRF such as SBP decrease.