Evaluation of Three Diagnostic Algorithms to Reduce Normal Scan Rates, Radiation Exposure and Costs in Patients with Suspected Chronic Coronary Syndrome Referred for 82Rb-Positron Emission Tomography (Rb-PET)
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Background: The majority of functional ischemia tests in patients with suspected chronic coronary syndromes (CCS) yield normal results. Implementing gatekeepers for patient preselection, such as pretest probability (PTP) and/or coronary artery calcium score (CACS), could reduce the number of normal scan results, radiation exposure and costs. However, the efficacy and safety of these approaches remain unclear.
Methods: Three diagnostic algorithms based on PTP, as summarised in the 2019 European Society of Cardiology (ESC) CCS guidelines, were retrospectively applied to 1792 patients with suspected CCS referred for 82Rb-Positron Emission Tomography (Rb-PET): (1) defer testing if PTP ≤5%; (2) defer if PTP <15%; and (3) defer if PTP ≤5% or PTP 5-15% and CACS 0. The proportion of missed ischemia, number of scans and reduction of normal scan results, radiation exposure and costs were compared with the current gold standard (CACS+PET in every patient). Endpoints were defined as small ischemia (SDS ≥2) and relevant ischemia (≥10% of myocardium).
Results: The mean age of the patients was 65±11 years, and 43% were female. PTP ≤5% and <15% were present in 7.5% and 41.0%, respectively. Algorithm 1 reduced scans, radiation and costs by 7.5% without significantly missing ischemia (sensitivity/negative predictive value (NPV) 98.6%/99.7%). Algorithm 2 showed the largest reduction (41.0%), but sensitivity was significantly reduced (80.2%). Algorithm 3 demonstrated optimal performance, reducing radiation by 17.0% and costs by 17.3% without significantly missing ischemia suggesting excellent safety (sensitivity/NPV 98.0%/99.5%).
Conclusion: Using a diagnostic algorithm combining PTP and CACS (algorithm 3), the number of normal scan results, radiation exposure and costs could be significantly reduced without a significant increase in missed diagnoses suggesting similar outcome and excellent patients safety. Consequently, this approach could help to optimally allocate limited healthcare resources while maintaining patient's safety.