External Validation of the CRAX2MACE model

Introduction: Single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is frequently used to predict the risk of major adverse cardiovascular events (MACE). The CRAX2MACE score was designed to predict the 2-year risk of MACE (all-cause mortality, non-fatal myocardial infarction [MI] and late coronary revascularization) by combining clinical risk factors with SPECT MPI results in patients with suspected coronary artery disease (CAD). Given the dependence of CRAX2MACE performance on population characteristics, we performed an external validation of CRAX2MACE using local data.

Methods: Patients with suspected CAD who underwent SPECT MPI between 2014 and 2018 with follow-up for MACE were included (N=2319). The prediction performance for MACE within 2-years for CRAX2MACE was compared with stress and ischemic total perfusion deficit (TPD) using area under the receiver operating characteristic curve (AUC). Calibration was assessed with calibration plots, Brier score and the Hosmer-Lemeshow test.

Results: MACE occurred within 2 years in 158 (6.8%) patients. The AUC for predicting MACE at 2-years for CRAX2MACE was 0.72 (95% CI 0.68 – 0.76) and was significantly higher than stress TPD (AUC 0.66, 95% CI 0.62 – 0.71) and ischemic TPD (AUC 0.63, 95% CI 0.58 – 0.67, p<0.01 for both, Figure A). The model had acceptable goodness-of-fit (p=0.103) and was well-calibrated with a Brier score of 0.061 (Figure B). The AUC for prediction of MI or all-cause mortality at 2-years was also higher for CRAX2MACE (AUC 0.72, 95% CI 0.68-0.76) compared to stress TPD (AUC 0.64, 95% CI 0.59 – 0.69) or ischemic TPD (AUC 0.61, 95% CI 0.57 – 0.66, both p<0.01) Figure C.

Conclusions: CRAX2MACE had higher predictive performance for 2-year MACE and 2-year MI or all-cause mortality than quantitative perfusion in an external population. The model also demonstrated good calibration. Adaptation of the model with the use of machine learning or incorporation of calcium scoring may further improve its performance; however, it currently benefits from its simplicity and ease of application to routine patient care.

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