however, the potential role of CAC among individuals who have no risk factors (RFs) is less established. We sought to examine the relationship between the presence and burden of traditional RFs and CAC for the prediction of all-cause mortality. Methods and Results-The study cohort consisted of 44 052 consecutive asymptomatic individuals free of known coronary heart disease referred for computed tomography for the assessment of CAC. The following RFs were considered: (1) current cigarette smoking, (2) dyslipidemia, (3) diabetes mellitus, (4) hypertension, and (5) family history of coronary heart disease. Patients were followed for a mean of 5.6±2.6 years for the primary end point of all-cause mortality. Among individuals who had no RF, Cox proportional model adjusted for age and sex identified that increasing CAC scores were associated with 3.00-to 13.38-fold higher mortality risk. The lowest survival rate was observed in those with no CAC and no RF, whereas those with CAC≥400 and ≥3 RFs had the highest all-cause fatality rate. Notably, individuals with no RF and CAC≥400 had a substantially higher mortality rate compared with individuals with ≥3 RFs in the absence of CAC (16.89 versus 2.72 per 1000 person-years). Conclusions-By highlighting that individuals without RFs but elevated CAC have a substantially higher event rates than those who have multiple RFs but no CAC, these findings challenge the exclusive use of traditional risk assessment algorithms for guiding the intensity of primary prevention therapies. (Circ Cardiovasc Imaging. 2012; 5:467-473).