Zhou J, et al. - Using traditional risk factors with coronary calcium score and epicardial fat volume (EFV), researchers developed a new model to approximate pretest probability of obstructive coronary artery disease. Further, they assessed along proposed models in Chinese patients who had coronary computed tomography angiography. Findings suggested achievement of higher accuracy and efficacy in estimating pretest probability of obstructive coronary artery disease with the addition of EFV to conventional risk factors and coronary calcium score, which may improve initial management of stable chest pain.

Methods

• Researchers used multivariate logistic regression to derive the new models from 5,743 consecutive patients; validation was done in an internal cohort using invasive coronary angiography as the outcome and an external cohort with clinical outcome data.
• They validated and compared the performance of models by calculating Hosmer-Lemeshow goodness-of-fit test, area under the receiver operating characteristic curve, integrated discrimination improvement and net reclassification improvement.

Results

• Compared with conventional risk factors and coronary calcium score, EFV displayed better performance in predicting the risk (area under the receiver operating characteristic curve increased from 0.856 to 0.874, integrated discrimination improvement 0.0487, net reclassification improvement 0.1181; P < 0.0001 for all).
• Five predictors were included in the final model: age, sex, symptom, coronary calcium score, and EFV.
• Researchers achieved good internal validation and external validation of the new model, with positive net reclassification improvement and integrated discrimination improvement, excellent area under the receiver operating characteristic curve, and favorable calibration.
• In addition, they observed a better prediction of clinical outcome with the new model that resulted in more cost-effective risk stratification to optimize decision-making of later diagnosis and treatment.