The ideal CV risk assessment would correctly reclassify all intermediate risk individuals into a low or high risk category based on future CVD event rates. Individuals at intermediate CV risk have the greatest potential benefit for any test that improves the b The FRS is available at: https://www.thecalculator.co/health/Framingham-Risk-Score-Calculator-for-Coronary-Heart-Disease- c The PCE is available at: https://clincalc.com/cardiology/ascvd/pooledcohort.aspx d The VARS-CVD is available at: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5561663/ performance of a 10-year risk calculator. However, there is no prospective evidence that additional risk refinement tools improve patient-centered outcomes. Lin et al. (2018) demonstrated that the addition of CAC to the FRS improved 10-year CVD event prediction by a very small change in the C statistic (change in area under the curve [AUC]: 0.02, 95% confidence interval [CI]: not reported).[29] This systematic review found similar results when CAC was added to the calibrated Pooled Cohort Equation (cPCE) (change in AUC: 0.02, 95% CI: 0.0 0.05).[29] Yeboah et al. (2016) was the largest of the retrospective studies included in Lin et al. related to the addition of CAC testing.[30] It assessed net reclassification improvement by adding CAC to the cPCE within the pre-existing study data from the Multi-Ethnic Study of Atherosclerosis cohort of over 5,000 subjects.[30] When actual patient events were compared with CAC scoring results, 58 patients were correctly reclassified, and 292 patients were incorrectly reclassified. Assuming a statin relative risk reduction of 25% for major adverse cardiac events (MACE), 15 patients who experienced a future event would benefit, whereas the remaining 335 patients would potentially be subjected to risks of treatment without benefit. The Work Group encourages shared decision making on the risks and benefits surrounding the use of CAC for enhancing CV risk assessment. Prospective studies of CAC screening do show improvement in the net reclassification index.