Author + information
- Received November 16, 2016
- Revision received November 30, 2016
- Accepted December 1, 2016
- Published online February 27, 2017.
- Nasrien E. Ibrahim, MDa,
- James L. Januzzi Jr., MDa,b,∗ (, )
- Craig A. Magaret, MSc,
- Hanna K. Gaggin, MD, MPHa,b,
- Rhonda F. Rhyne, BPharm, MBAc,
- Parul U. Gandhi, MDd,
- Noreen Kelly, MDe,
- Mandy L. Simon, DNP, FNP-BCa,
- Shweta R. Motiwala, MDe,
- Arianna M. Belcher, MSa and
- Roland R.J. van Kimmenade, MD, PhDf
- aMassachusetts General Hospital, Division of Cardiology, Boston, Massachusetts
- bHarvard Clinical Research Institute, Cardiometabolic Trials, Boston, Massachusetts
- cPrevencio, Inc., Kirkland, Washington
- dYale University, Cardiology, New Haven, Connecticut
- eBrigham and Women's Hospital, Cardiology, Boston, Massachusetts
- fDepartment of Cardiology, Radboud University Medical Centre, Nijmegen, the Netherlands
- ↵∗Address for correspondence:
Dr. James L. Januzzi Jr., Division of Cardiology, Massachusetts General Hospital, 32 Fruit Street, Yawkey 5984, Boston, Massachusetts 02114.
Background Noninvasive models to predict the presence of coronary artery disease (CAD) may help reduce the societal burden of CAD.
Objectives From a prospective registry of patients referred for coronary angiography, the goal of this study was to develop a clinical and biomarker score to predict the presence of significant CAD.
Methods In a training cohort of 649 subjects, predictors of ≥70% stenosis in at least 1 major coronary vessel were identified from >200 candidate variables, including 109 biomarkers. The final model was then validated in a separate cohort (n = 278).
Results The scoring system consisted of clinical variables (male sex and previous percutaneous coronary intervention) and 4 biomarkers (midkine, adiponectin, apolipoprotein C-I, and kidney injury molecule–1). In the training cohort, elevated scores were predictive of ≥70% stenosis in all subjects (odds ratio [OR]: 9.74; p < 0.001), men (OR: 7.88; p <0.001), women (OR: 24.8; p < 0.001), and those with no previous CAD (OR: 8.67; p < 0.001). In the validation cohort, the score had an area under the receiver-operating characteristic curve of 0.87 (p < 0.001) for coronary stenosis ≥70%. Higher scores were associated with greater severity of angiographic stenosis. At optimal cutoff, the score had 77% sensitivity, 84% specificity, and a positive predictive value of 90% for ≥70% stenosis. Partitioning the score into 5 levels allowed for identifying or excluding CAD with >90% predictive value in 42% of subjects. An elevated score predicted incident acute myocardial infarction during 3.6 years of follow up (hazard ratio: 2.39; p < 0.001).
Conclusions We described a clinical and biomarker score with high accuracy for predicting the presence of anatomically significant CAD. (The CASABLANCA Study: Catheter Sampled Blood Archive in Cardiovascular Diseases; NCT00842868)
This work was supported by a grant from Prevencio, Inc. Dr. Ibrahim is supported by the Dennis and Marilyn Barry Fellowship in Cardiology. Dr. Januzzi is supported in part by the Hutter Family Professorship in Cardiology; has received grant support from Siemens, Singulex, and Prevencio; consulting income from Roche Diagnostics, Critical Diagnostics, Sphingotec, Phillips, and Novartis; and participates in clinical endpoint committees/data safety monitoring boards for Novartis, Amgen, Janssen, and Boehringer Ingelheim. Dr. Gaggin is supported in part by the Ruth and James Clark Fund for Cardiac Research Innovation; and has received grant support from Roche and Portola; consulting income from Roche Diagnostics, American Regent, Amgen, Boston Heart Diagnostics, and Critical Diagnostics; and research payments for clinical endpoint committees for EchoSense and RadioMeter. Mr. Magaret is a consultant to Prevencio, Inc. Ms. Rhyne is an employee of Prevencio, Inc. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose. Drs. Ibrahim and Januzzi contributed equally to this work. Sanjay Kaul, MD, served as Guest Editor for this paper.
- Received November 16, 2016.
- Revision received November 30, 2016.
- Accepted December 1, 2016.
- American College of Cardiology Foundation