Table 4.

AUC and NRI to predict CAC presence

Sex Age	n	AUC Model 1 (95% CI)	AUC Model 2 (95% CI)	Categorical NRI Low Risk Cutoff	Categorical NRI High Risk Cutoff	Categorical NRI (95% CI)	Continuous NRI (95% CI)
Female 50–60	964	0.630 (0.588, 0.671)	0.661 (0.6204, 0.701)	0.15	0.35	0.109 (0.037, 0.185)	0.363 (0.218, 0.512)
Male 40–50	931	0.673 (0.633, 0.712)	0.690 (0.651, 0.729)	0.15	0.35	0.092 (0.015, 0.175)	0. 325 (0.187, 0.476)
Female 44–54	1062	0.680 (0.638, 0.723)	0.688 (0.645, 0.732)	0.10	0.25	0.071 (-0.008, 0.150)	0.186 (0.004, 0.353)
Male 34–44	699	0.694 (0.639, 0.749)	0.697 (0.645, 0.750)	0.10	0.25	0.143 (0.047, 0.243)	0.263 (0.049, 0.477)

AUC and NRI for the addition of GRS to traditional risk factors to predict CAC presence. Model 1 included age, sex, and number of traditional risk factors as predictors. Model 2 included age, sex, number of traditional risk factors, and GRS as predictors.

AUC = area under the receiver operator characteristic curve, NRI = net reclassification improvement, GRS = genetic risk score,