A novel tool in which clinical risk factors and coronary artery calcium score (CACS) are added to standard pre-test probability (PTP) modeling was found to improve risk prediction in suspected obstructive coronary artery disease (CAD), according to a study published in the Journal of the American College of Cardiology.

With obstructive CAD prevalence declining among symptomatic patients who undergo diagnostic testing, more personalized diagnostic strategies are warranted to optimize clinical care and improve outcomes. Investigators sought to develop a simple tool to enhance CAD prediction and the ability to rule-out patients with low likelihood of disease.

The standard Diamond-Forrester-based PTP model (based on sex, age, and symptoms variables) served as the base for the new tool. This newly developed tool consists of a risk factor-weighted clinical likelihood (RF-CL) model that takes into account PTP and cardiovascular risk factors (ie, hypertension, smoking, diabetes, and dyslipidemia), and a CACS-weighted clinical likelihood (CACS-CL) model.


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The tool was developed in a Danish multicenter training cohort of 41,177 symptomatic patients with suspected CAD (mean age, 57.0±11.4 years; 45.6% men) who had an initial coronary computed tomography angiography performed between 2008 and 2017. Validation studies were conducted on 3 different North American and European cohorts comprising a total of 15,411 patients (mean age, 59.2±10.6 years; 48.8% men) with similar clinical circumstances.

Across the validation cohorts, the prevalence of obstructive CAD (ie, ≥50% diameter stenosis) was more accurately predicted by the RF-CL and CACS-CL models compared with the PTP model, as indicated by increases in the area under the receiver-operative characteristic curves (PTP: 72.3; 95% CI, 71.0-73.6; RF-CL: 74.9; 95% CI, 73.7-76.1; and CACS-CL: 84.9; 95% CI, 84.0-85.9).

The tool allowed for reclassification of many patients to a low clinical likelihood of CAD (RF-CL, 28%; CACS-CL, 54%; PTP, 11%), for whom there are no further indications for testing.

Study limitations include potential selection bias, possible under-representation of individuals with severe obesity or renal disease, and the fact that validation was carried out in predominantly white European and North American participants.

“We developed a simple RF-CL and CACS-CL tool, which enables a more accurate prediction and discrimination of patients with suspected obstructive CAD,” noted the authors. “Further studies are needed to evaluate the predictive value of this simple assessment method in well-defined subgroups of patients at risk of CAD.”

Funding and Conflicts of Interest Disclosures:

Please see original article for funding and conflict of interest information.

Reference

Winther S, Schmidt SE, Mayrhofer T, et al. Incorporating coronary calcification into pre-test assessment of the likelihood of coronary artery disease. J Am Coll Cardiol. 2020;76(21):2421-2432. doi:10.1016/j.jacc.2020.09.585