Predictive model for high-risk coronary artery disease: Insights from the PROMISE trial

James J. Jang, Manjushri Bhapkar, Adrian Coles, Sreekanth Vemulapalli, Christopher B. Fordyce, Kerry L. Lee, James E. Udelson, Udo Hoffmann, Jean Claude Tardif, W. Schuyler Jones, Daniel B. Mark, Vincent L. Sorrell, Andrey Espinoza, Pamela S. Douglas, Manesh R. Patel

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Background: Patients with high-risk coronary artery disease (CAD) may be difficult to identify. Methods: Using the PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) cohort randomized to coronary computed tomographic angiography (n=4589), 2 predictive models were developed for high-risk CAD, defined as left main stenosis (≥50% stenosis) or either (1) ≥50% stenosis [50] or (2) ≥70% stenosis [70] of 3 vessels or 2-vessel CAD involving the proximal left anterior descending artery. Pretest predictors were examined using stepwise logistic regression and assessed for discrimination and calibration. Results: High-risk CAD was identified in 6.6% [50] and 2.4% [70] of patients. Models developed to predict high-risk CAD discriminated well: [50], bias-corrected C statistic=0.73 (95% CI, 0.71-0.76); [70], bias-corrected C statistic=0.73 (95% CI, 0.68-0.77). Variables predictive of CAD in both models included family history of premature CAD, age, male sex, lower glomerular filtration rate, diabetes mellitus, elevated systolic blood pressure, and angina. Additionally, smoking history was predictive of [50] CAD and sedentary lifestyle of [70] CAD. Both models characterized high-risk CAD better than the Pooled Cohort Equation (area under the curve=0.70 and 0.71 for [50] and [70], respectively) and Diamond-Forrester risk scores (area under the curve=0.68 and 0.71, respectively). Both [50] and [70] CAD was associated with more frequent invasive interventions and adverse events than non-high-risk CAD (all P<0.0001). Conclusions: In contemporary practice, 2.4% to 6.6% of stable, symptomatic patients requiring noninvasive testing have high-risk CAD. A simple combination of pretest clinical variables improves prediction of high-risk CAD over traditional risk assessments.

Original languageEnglish
Article numbere007940
JournalCirculation: Cardiovascular Imaging
Volume12
Issue number2
DOIs
StatePublished - Feb 1 2019

Bibliographical note

Funding Information:
This project was supported by grants R01HL098237, R01HL098236, R01HL98305, and R01HL098235 from the National Heart, Lung, and Blood Institute (NHLBI). The authors are solely responsible for the design and conduct of this study, all study analyses, the drafting and editing of the article, and its final contents. This article does not necessarily represent the official views of NHLBI.

Funding Information:
This project was supported by grants R01HL098237, R01HL098236, R01HL98305, and R01HL098235 from the National Heart, Lung, and Blood Institute (NHLBI).

Publisher Copyright:
© 2019 American Heart Association, Inc.

Keywords

  • angiography
  • coronary artery disease
  • risk assessment

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Cardiology and Cardiovascular Medicine

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