Posterior Probabilities in Sequential Testing Improve Clinical Cardiovascular Risk Prediction Using Carotid Total Plaque Area and C-Statistics

Background: Risk prediction for myocardial infarction currently uses global risk assessment tools (PROCAM, SCORE or NCEP III). Their sensitivity is however low (about 33%). Emerging risk assessment tools are increasingly applied, but the incremental value is debated. Aims: To develop a risk prediction model based on posterior test probabilities (PTP) and to determine the statistical significance of the incremental gain using Receiver Operating Characteristic (ROC) curve comparison in combination with the Bayes theorem. Methods: In a primary care cohort, both NCEP III and total carotid plaque area (TPA) were used to calculate 10-year risk, and combined posttest risk probabilities for myocardial infarction (TPA-PTP) were combined by using Bayes theorem. ROC curves were compared for NCEP III, TPA, and TPA-PTP. Results: A total of 684 subjects with a mean age of 50 years were followed for 3.3 ± 1.8 years. Thirteen myocardial infarctions occurred. Sensitivity was 31% for NCEP III and 62% for TPA >0.55 cm2 and 39% for TPAPTP; specificity was 89%, 75% and 79% respectively (all p = NS). AUC was 0.68 for NCEP III and 0.75 for TPA-PTP (p = 0.0034). Net reclassification improvement analysis yielded a result of +18.25%. Conclusions: ROC curve comparison is a conservative approach to estimating the value of emerging risk assessment tools in the primary prevention of myocardial infarction. Despite a limited number of individuals and few myocardial infarctions that occurred during follow-up, TPA-PTP yielded a statistically significant incremental value over NCEP III. This was due to the integration of posttest risk calculation into risk prediction. PTP risk estimates using published sensitivities and specificities of an emerging test may be used to compare ROC curves and improve the assessment of the clinical utility of new emerging risk assessment tools.