Improved near-term coronary artery disease risk classification with gated stress myocardial perfusion SPECT.

OBJECTIVES We compared analytical approaches to estimate the added value of myocardial perfusion single-photon emission computed tomography (MPS) variables in estimating coronary artery disease (CAD) outcomes. BACKGROUND Stress MPS markers of regional ischemia are strong estimators of prognosis. Evidence published to date has not compared analytical methods to establish the added value of stress MPS and to define a clinically meaningful approach to detect improve classification of risk. METHODS A total of 4,575 patients were consecutively and prospectively enrolled in the Myoview Prognosis Registry. Multivariable Cox proportional hazards model were employed to estimate CAD death or myocardial infarction (MI). Risk reclassification methods were also calculated. RESULTS In risk-adjusted models (including age, sex, presenting symptoms, stress type, CAD history, and risk factors), stress MPS ischemia, rest and post-stress left ventricular ejection fraction (LVEF) (all p < 0.0001) were all significant estimators of CAD death or MI. In this multivariable model, 34% of the model chi-square was contributed by MPS ischemia. In receiver-operating characteristic curve analysis, the area under the curve increased from 0.61 to 0.66 when rest and post-stress LVEF were combined with pre-test CAD likelihood (p < 0.0001), increasing to 0.69 for MPS ischemia (p < 0.0001). The net reclassification improvement (NRI) by adding the Duke Treadmill Score (DTS) to a model including pre-test CAD likelihood was 0.112. The cost per NRI was $57 for the exercise test as compared with an office visit for risk stratification purposes. Further, the NRI by adding MPS ischemia to a model with the DTS and pre-test CAD likelihood was 0.358. The cost per NRI was $615 for the stress MPS as compared with an exercise test. CONCLUSIONS Stress-induced ischemia is independently predictive of near-term CAD outcomes. Analytical approaches that establish the reclassification of events provide a unique approach and may serve as a quality imaging metric for estimation of improved health outcomes for stress MPS as well as for comparison to other imaging modalities.

[1]  L. Shaw,et al.  34th Bethesda Conference: Task force #5--Is atherosclerosis imaging cost effective? , 2003, Journal of the American College of Cardiology.

[2]  Paul M. Ridker,et al.  Development and Validation of Improved Algorithms for the Assessment of Global Cardiovascular Risk in Women , 2007 .

[3]  M. D. Di Carli,et al.  New technology for noninvasive evaluation of coronary artery disease. , 2007, Circulation.

[4]  David Litaker,et al.  Association of socioeconomic status with functional capacity, heart rate recovery, and all-cause mortality. , 2006, JAMA.

[5]  D. Berman,et al.  Comparison of the Short‐Term Survival Benefit Associated With Revascularization Compared With Medical Therapy in Patients With No Prior Coronary Artery Disease Undergoing Stress Myocardial Perfusion Single Photon Emission Computed Tomography , 2003, Circulation.

[6]  J J Bax,et al.  Diagnostic and clinical perspectives of fusion imaging in cardiology: is the total greater than the sum of its parts? , 2005, Heart.

[7]  Guido Germano,et al.  Optimal Medical Therapy With or Without Percutaneous Coronary Intervention to Reduce Ischemic Burden: Results From the Clinical Outcomes Utilizing Revascularization and Aggressive Drug Evaluation (COURAGE) Trial Nuclear Substudy , 2008, Circulation.

[8]  D. Berman,et al.  Prognostic value of multidetector coronary computed tomographic angiography for prediction of all-cause mortality. , 2007, Journal of the American College of Cardiology.

[9]  M. Pencina,et al.  Evaluating the added predictive ability of a new marker: From area under the ROC curve to reclassification and beyond , 2008, Statistics in medicine.

[10]  D. Berman,et al.  Prognosis by coronary computed tomographic angiography: matched comparison with myocardial perfusion single-photon emission computed tomography. , 2008, Journal of cardiovascular computed tomography.

[11]  D. Berman,et al.  Cardiovascular disease risk stratification with stress single-photon emission computed tomography technetium-99m tetrofosmin imaging in patients with the metabolic syndrome and diabetes mellitus. , 2006, The American journal of cardiology.

[12]  Zahi A Fayad,et al.  Atherothrombosis and high-risk plaque: part I: evolving concepts. , 2005, Journal of the American College of Cardiology.

[13]  P. Marzullo,et al.  Extension of myocardial necrosis differently affects MIBG retention in heart failure caused by ischaemic heart disease or by dilated cardiomyopathy , 2005, European Journal of Nuclear Medicine and Molecular Imaging.

[14]  E J Topol,et al.  Cause of death in clinical research: time for a reassessment? , 1999, Journal of the American College of Cardiology.

[15]  L. Shaw,et al.  Prognostic value of normal exercise and adenosine (99m)Tc-tetrofosmin SPECT imaging: results from the multicenter registry of 4,728 patients. , 2003, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[16]  N. Cook.  Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. , 2008, Clinical chemistry.

[17]  Daniel S. Berman,et al.  Prognostic value of poststress left ventricular volume and ejection fraction by gated myocardial perfusion SPECT in women and men: Gender-related differences in normal limits and outcomes , 2006, Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology.

[18]  G Germano,et al.  Prediction of myocardial infarction versus cardiac death by gated myocardial perfusion SPECT: risk stratification by the amount of stress-induced ischemia and the poststress ejection fraction. , 2001, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[19]  Mark A. Hlatky,et al.  ACCF/AHA 2007 Clinical Expert Consensus Document on Coronary Artery Calcium Scoring By Computed Tomography in Global Cardiovascular Risk Assessment and in Evaluation of Patients With Chest Pain , 2007 .

[20]  Frank P. DiFilippo,et al.  ASNC IMAGING GUIDELINES FOR NUCLEAR CARDIOLOGY PROCEDURES Single photon-emission computed tomography , 2010 .

[21]  L. Shaw,et al.  Prognostic value of gated myocardial perfusion SPECT , 2004, Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology.

[22]  Nancy R Cook,et al.  Advances in Measuring the Effect of Individual Predictors of Cardiovascular Risk: The Role of Reclassification Measures , 2009, Annals of Internal Medicine.

[23]  D. Levy,et al.  Prediction of coronary heart disease using risk factor categories. , 1998, Circulation.

[24]  D. Berman,et al.  Predicting therapeutic benefit from myocardial revascularization procedures: Are measurements of both resting left ventricular ejection fraction and stress-induced myocardial ischemia necessary? , 2006, Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology.

[25]  Ralph Weissleder,et al.  Molecular imaging of cardiovascular disease. , 2007, Circulation.

[26]  M. Pencina,et al.  C-Reactive Protein and Reclassification of Cardiovascular Risk in the Framingham Heart Study , 2008, Circulation. Cardiovascular quality and outcomes.

[27]  L. Shaw,et al.  Ethnic differences in the prognostic value of stress technetium-99m tetrofosmin gated single-photon emission computed tomography myocardial perfusion imaging. , 2005, Journal of the American College of Cardiology.

[28]  N. Cook,et al.  Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score. , 2007, JAMA.