TY - JOUR
T1 - Development and validation of ischemia risk scores
AU - Miller, Robert J.H.
AU - Rozanski, Alan
AU - Slomka, Piotr J.
AU - Han, Donghee
AU - Gransar, Heidi
AU - Hayes, Sean W.
AU - Friedman, John D.
AU - Thomson, Louise E.J.
AU - Berman, Daniel S.
N1 - Publisher Copyright:
© 2022, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.
PY - 2023/2
Y1 - 2023/2
N2 - Background: The likelihood of ischemia on myocardial perfusion imaging is central to physician decisions regarding test selection, but dedicated risk scores are lacking. We derived and validated two novel ischemia risk scores to support physician decision making. Methods: Risk scores were derived using 15,186 patients and validated with 2,995 patients from a different center. Logistic regression was used to assess associations with ischemia to derive point-based and calculated ischemia scores. Predictive performance for ischemia was assessed using area under the receiver operating characteristic curve (AUC) and compared with the CAD consortium basic and clinical models. Results: During derivation, the calculated ischemia risk score (0.801) had higher AUC compared to the point-based score (0.786, p < 0.001). During validation, the calculated ischemia score (0.716, 95% CI 0.684− 0.748) had higher AUC compared to the point-based ischemia score (0.699, 95% CI 0.666− 0.732, p = 0.016) and the clinical CAD model (AUC 0.667, 95% CI 0.633− 0.701, p = 0.002). Calibration for both ischemia scores was good in both populations (Brier score < 0.100). Conclusions: We developed two novel risk scores for predicting probability of ischemia on MPI which demonstrated high accuracy during model derivation and in external testing. These scores could support physician decisions regarding diagnostic testing strategies.
AB - Background: The likelihood of ischemia on myocardial perfusion imaging is central to physician decisions regarding test selection, but dedicated risk scores are lacking. We derived and validated two novel ischemia risk scores to support physician decision making. Methods: Risk scores were derived using 15,186 patients and validated with 2,995 patients from a different center. Logistic regression was used to assess associations with ischemia to derive point-based and calculated ischemia scores. Predictive performance for ischemia was assessed using area under the receiver operating characteristic curve (AUC) and compared with the CAD consortium basic and clinical models. Results: During derivation, the calculated ischemia risk score (0.801) had higher AUC compared to the point-based score (0.786, p < 0.001). During validation, the calculated ischemia score (0.716, 95% CI 0.684− 0.748) had higher AUC compared to the point-based ischemia score (0.699, 95% CI 0.666− 0.732, p = 0.016) and the clinical CAD model (AUC 0.667, 95% CI 0.633− 0.701, p = 0.002). Calibration for both ischemia scores was good in both populations (Brier score < 0.100). Conclusions: We developed two novel risk scores for predicting probability of ischemia on MPI which demonstrated high accuracy during model derivation and in external testing. These scores could support physician decisions regarding diagnostic testing strategies.
KW - Cardiac stress testing
KW - Coronary artery disease
KW - Myocardial ischemia
KW - SPECT myocardial perfusion imaging
UR - https://www.scopus.com/pages/publications/85128950779
U2 - 10.1007/s12350-022-02976-9
DO - 10.1007/s12350-022-02976-9
M3 - Article
AN - SCOPUS:85128950779
SN - 1071-3581
VL - 30
SP - 324
EP - 334
JO - Journal of Nuclear Cardiology
JF - Journal of Nuclear Cardiology
IS - 1
ER -