Utility of coronary artery calcium in refining 10-year ASCVD risk prediction using a Thai CV risk score

Author:

Tiansuwan Noppanat,Sasiprapha Thinnakrit,Jongjirasiri Sutipong,Unwanatham Nattawut,Thakkinstian Ammarin,Laothamatas Jiraporn,Limpijankit Thosaphol

Abstract

BackgroundCoronary artery calcium (CAC) scanning is a valuable additional tool for calculating the risk of cardiovascular (CV) events. We aimed to determine if a CAC score could improve performance of a Thai CV risk score in prediction of 10-year atherosclerotic cardiovascular disease (ASCVD) risk for asymptomatic patients with CV risk factors.MethodsThis was a retrospective cohort study that enrolled asymptomatic patients with CV risk factors who underwent CAC scans between 2005 and 2013. The patients were classified as low-, intermediate-, or high-risk (<10%, 10%–<20%, and ≥20%, respectively) of having ASCVD within 10-years based on a Thai CV risk score. In each patient, CAC score was considered as a categorical variable (0, 1–99, and ≥100) and natural-log variable to assess the risk of developing CV events (CV death, non-fatal MI, or non-fatal stroke). The C statistic and the net reclassification improvement (NRI) index were applied to assess whether CAC improved ASCVD risk prediction.ResultsA total of 6,964 patients were analyzed (mean age: 59.0 ± 8.4 years; 63.3% women). The majority of patients were classified as low- or intermediate-risk (75.3% and 20.5%, respectively), whereas only 4.2% were classified as high-risk. Nearly half (49.7%) of patients had a CAC score of zero (no calcifications detected), while 32.0% had scores of 1–99, and 18.3% of ≥100. In the low- and intermediate-risk groups, patients with a CAC ≥100 experienced higher rates of CV events, with hazard ratios (95% CI) of 1.95 (1.35, 2.81) and 3.04 (2.26, 4.10), respectively. Incorporation of ln(CAC + 1) into their Thai CV risk scores improved the C statistic from 0.703 (0.68, 0.72) to 0.716 (0.69, 0.74), and resulted in an NRI index of 0.06 (0.02, 0.10). To enhance the performance of the Thai CV risk score, a revision of the CV risk model was performed, incorporating ln(CAC + 1), which further increased the C statistic to 0.771 (0.755, 0.788).ConclusionThe addition of CAC to traditional risk factors improved CV risk stratification and ASCVD prediction. Whether this adjustment leads to a reduction in CV events and is cost-effective will require further assessment.

Publisher

Frontiers Media SA

Subject

Cardiology and Cardiovascular Medicine

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