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Prediction of future cardiovascular disease with an equation to estimate apolipoprotein B in patients with high cardiovascular risk: an analysis from the TNT and IDEAL study.
Lipids in Health and Disease 2017 August 23
BACKGROUND: Apolipoprotein B (apoB) is known to be a more powerful predictor of cardiovascular disease than conventional lipids. We aimed to determine the clinical relevance of a newly developed equation to estimate serum apoB levels based on total cholesterol, HDL cholesterol, and triglycerides in patients with high cardiovascular risk.
METHODS: The occurrence of a major cardiovascular event (MCVE) was assessed using the data from the Treating to New Targets (TNT) and Incremental Decrease in End points through Aggressive Lipid lowering (IDEAL) trials.
RESULTS: Pooled analysis of these two data sets showed that both directly-measured apoB (HR per 1-SD (95% CI): 1.16 (1.11-1.21), P < 0.001) and apoB estimated from the eq. (HR per 1-SD (95% CI): 1.14 (1.09-1.19), P < 0.001) were significantly associated with the development of a future MCVE. Prediction of MCVEs by the apoB eq. (C statistic 0.650) was nearly identical to that of directly-measured apoB (0.651). In addition, the net reclassification indices indicated no difference in the prediction of MCVEs between models including the apoB equation and directly-measured apoB (1% (-1.3-4.0), P = 0.31).
CONCLUSIONS: Our equation to predict apoB levels showed MCVE risk prediction comparable to directly-measured apoB in high risk patients with previous coronary heart disease.
METHODS: The occurrence of a major cardiovascular event (MCVE) was assessed using the data from the Treating to New Targets (TNT) and Incremental Decrease in End points through Aggressive Lipid lowering (IDEAL) trials.
RESULTS: Pooled analysis of these two data sets showed that both directly-measured apoB (HR per 1-SD (95% CI): 1.16 (1.11-1.21), P < 0.001) and apoB estimated from the eq. (HR per 1-SD (95% CI): 1.14 (1.09-1.19), P < 0.001) were significantly associated with the development of a future MCVE. Prediction of MCVEs by the apoB eq. (C statistic 0.650) was nearly identical to that of directly-measured apoB (0.651). In addition, the net reclassification indices indicated no difference in the prediction of MCVEs between models including the apoB equation and directly-measured apoB (1% (-1.3-4.0), P = 0.31).
CONCLUSIONS: Our equation to predict apoB levels showed MCVE risk prediction comparable to directly-measured apoB in high risk patients with previous coronary heart disease.
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