title: A Clinical and Biomarker Scoring System to Predict the Presence of Obstructive Coronary Artery Disease.
abstract: BACKGROUND
  Noninvasive models to predict the presence of coronary artery disease (CAD) may help reduce the societal burden of CAD.
  
  
  OBJECTIVE
  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).
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Boston, Massachusetts.
authors.forename: Nasrien E
authors.initials: NE
authors.lastname: Ibrahim
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Boston, Massachusetts; Harvard Clinical Research Institute, Cardiometabolic Trials, Boston, Massachusetts. Electronic address: jjanuzzi@partners.org.
authors.forename: James L
authors.initials: JL
authors.lastname: Januzzi
authors.affiliation: Prevencio, Inc., Kirkland, Washington.
authors.forename: Craig A
authors.initials: CA
authors.lastname: Magaret
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Boston, Massachusetts; Harvard Clinical Research Institute, Cardiometabolic Trials, Boston, Massachusetts.
authors.forename: Hanna K
authors.initials: HK
authors.lastname: Gaggin
authors.affiliation: Prevencio, Inc., Kirkland, Washington.
authors.forename: Rhonda F
authors.initials: RF
authors.lastname: Rhyne
authors.affiliation: Yale University, Cardiology, New Haven, Connecticut.
authors.forename: Parul U
authors.initials: PU
authors.lastname: Gandhi
authors.affiliation: Brigham and Women's Hospital, Cardiology, Boston, Massachusetts.
authors.forename: Noreen
authors.initials: N
authors.lastname: Kelly
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Boston, Massachusetts.
authors.forename: Mandy L
authors.initials: ML
authors.lastname: Simon
authors.affiliation: Brigham and Women's Hospital, Cardiology, Boston, Massachusetts.
authors.forename: Shweta R
authors.initials: SR
authors.lastname: Motiwala
authors.affiliation: Massachusetts General Hospital, Division of Cardiology, Boston, Massachusetts.
authors.forename: Arianna M
authors.initials: AM
authors.lastname: Belcher
authors.affiliation: Department of Cardiology, Radboud University Medical Centre, Nijmegen, the Netherlands.
authors.forename: Roland R J
authors.initials: RRJ
authors.lastname: van Kimmenade
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000097:blood; D015331:Cohort Studies; D003324:Coronary Artery Disease / Q000097:blood / Q000175:diagnosis* / Q000209:etiology; D023921:Coronary Stenosis / Q000097:blood / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve
chemical_list: D015415:Biomarkers
keywords: diagnosis; myocardial infarction; negative predictive value; positive predictive value; stenosis