• 2 ‘Clinical Likelihood’ Models Found to Improve CAD Risk Prediction Over Pretest Probability, Study Finds

    Two predictive models that estimate the clinical likelihood of obstructive coronary artery disease (CAD) have been found to improve outcome prediction compared with the basic pretest probability (PTP) model.

    Utilization of the risk factor-weighted clinical likelihood model (RF-CL) and the coronary artery calcium score–weighted clinical likelihood model (CACS-CL) led to the reclassification of substantially more patients into the group with very low likelihood (≤5%) of CAD with no further testing recommended.

    Despite this reclassification with the RF-CL (45%) or CACS-CL (60%) models compared with PTP (18%), the annualized event rates of myocardial infarction and death were low using all three models.

    The event rate for RF-CL was 0.51% (95% confidence interval [CI]: 0.46% to 0.56%), CACS-CL was 0.48% (95% CI: 0.44% to 0.56%), and PTP was 0.37% (95% CI: 0.31% to 0.44%).

    The findings were published Monday online ahead of the Nov. 22 issue of the Journal of the American College of Cardiology.

    Study methodology

    Led by Simon Winther, MD, PhD from the Gødstrup Hospital and Aarhus University, both in Denmark, the authors wrote that the assessment of the new models’ prognostic value could help clarify the 2019 European Society of Cardiology (ESC) guidelines.

    These guidelines introduced a novel concept of clinical likelihood of CAD as a more comprehensive assessment of CAD probability.

    The team utilized two large cohorts of patients without previously diagnosed CAD presenting with symptoms suggestive of obstructive CAD who were referred for noninvasive testing.

    These cohorts were the WDHR (Western Denmark Heart Registry) and the PROMISE (Prospective Multi-center Imaging Study for Evaluation of Chest Pain).

    The WDHR cohort included patients who underwent first-time coronary computed tomography angiography (CTA) from 2008 to 2017 in all 13 hospitals in the western part of Denmark.

    The PROMISE cohort consisted of 10,003 patients from the randomized clinical trial performed in 193 North American centers from 2010 to 2013.

    The research team included only patients randomized to and undergoing coronary CTA with interpretable results and CACS performed (n = 3952).

    Follow-up details

    The WDHR patients were followed up through the Danish Civil Personal Register and Danish National Patient Registry, which contained mortality, hospital/outpatient diagnosis, and test information.

    End of follow-up for the WDHR cohort was June 30, 2018, or when the patient emigrated outside of Denmark. No patients were lost to follow-up.

    The PROMISE patients were followed up by visits performed at 60 days and then by telephone or mail at 6-month intervals after randomization for a minimum of 1 year.

    Follow-up was set to end October 31, 2014. In total, 121 (2.4%) patients were lost to follow-up.

    Overall findings

    Overall, a comparison of the predictive power of the three models using Harrell’s C-statistics demonstrated superiority of the RF-CL (0.64 [95% CI: 0.63-0.65]) and CACS-CL (0.69 [95% CI: 0.67-0.70]) compared with the PTP model (0.61 [95% CI: 0.60-0.62]).

    “The optimized RF-CL and CACS-CL models identify 2.5 and 3.3 times more patients, respectively, who may not benefit from further diagnostic testing,” the study concluded.

    “27% more patients with the RF-CL model and 42% more patients with the CACS-CL model would be deferred from testing due to very low likelihood of obstructive disease (≤5%) compared with the PTP model.”

    “Estimated cost-savings would amount to approximately $125 million (27% of $500 million) and $200 million (42% of $500 million) with the RF-CL and CACS-CL, respectively.”

    Encouragement and applause for study

    In an accompanying editorial, Khurram Nasir, MD, MPH, MSc, and Safi U. Khan, MD, MS, from the Houston Methodist DeBakey Heart and Vascular Center, recognized that adopting pragmatic clinical likelihood models that included classic risk factors alone or combined with CAC-guided sequential testing was difficult.

    However, they expressed encouragement and applause for the study, and reiterated the need for a well-designed clinical trial to clarify the impact of these promising strategies in comparison with current standard-of-care approaches.

    This was not only to identify the right patients for advanced imaging but also for determining how these strategies will affect subsequent patient outcomes.

    “We are confident that when such studies are conducted, PTPs that also account for traditional risk factors, such as CACSs, will most likely reduce the need for advanced anatomical and ischemia testing in most patients suspected of having CAD and will do so in a cost-effective manner,” they said.


    Winther S, Schmidt SE, Foldyna B, et al. Coronary Calcium Scoring Improves Risk Prediction in Patients With Suspected Obstructive Coronary Artery Disease. J Am Coll Cardiol 2022; 80:1965– 1977.

    Nasir K, Khan SU. Power of Zero as Gatekeeper for Stable Chest Pain Patients: Minimizing Losses and Maximizing Gains. J Am Coll Cardiol 2022;80:1978–1980.

    Image Credit: Rasi – stock.adobe.com

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