Abstract 3408: Coronary Calcium Predicts Events Better With Absolute Calcium Scores Than Age-gender Percentiles - The Multi-ethnic Study Of Atherosclerosis
Background: The presence and extent of coronary artery calcium (CAC) correlates with the overall magnitude of coronary atherosclerotic plaque burden and with the development of subsequent coronary events. In this study we aim to establish whether age-gender specific percentiles of CAC predict cardiovascular outcomes better than the actual CAC score.
Methods: MESA is a prospective cohort study of 6814 participants free of clinical cardiovascular disease at entry. Participants were followed for coronary heart disease (CHD) events including MI, angina, resuscitated cardiac arrest or CHD death. Time to incident CHD using Cox regression, and compared models using age and gender specific percentiles, with those using categories defined by commonly used groups (0, 1–100, 101– 400, 400+ Agatston units).
Results: There were 163 incident CHD events observed over a median of 3.75 years. Expressing CAC in terms of age and gender specific percentiles had significantly lower area under the ROC curve (AUC) than simply using overall score (for women: AUC 0.73 versus 0.76, p=0.044; for men: AUC 0.73 versus 0.77, p<0.001). Additionally, Akaike’s information criterion (AIC) indicated better model fit using the overall score. This was true using the variables continuously, or categorizing into four groups. Table 1⇓ displays the sample size, event rates, hazards ratios and AIC statistics for models using categories.
Conclusion: Using CAC in standard categories performed better than age and gender specific percentiles in terms of model fit and discrimination. Cut-points based on percentiles have the additional problem that they are study-specific, and we recommend using cut-points based on the absolute CAC amount. Further study based on a greater number of events may help elucidate which specific cutpoints are best, however at the moment, common clinical choices of 100 and 400 perform well.