Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: Propensity score-based analysis of diabetic and non-diabetic patients

Inge J. van den Hoogen, Alexander R. van Rosendael, Fay Y. Lin, Yao Lu, Aukelien C. Dimitriu-Leen, Jeff M. Smit, Arthur J.H.A. Scholte, Stephan Achenbach, Mouaz H. Al-Mallah, Daniele Andreini, Daniel S. Berman, Matthew J. Budoff, Filippo Cademartiri, Tracy Q. Callister, Hyuk Jae Chang, Kavitha Chinnaiyan, Benjamin J.W. Chow, Ricardo C. Cury, Augustin DeLago, Gudrun FeuchtnerMartin Hadamitzky, Joerg Hausleiter, Philipp A. Kaufmann, Yong Jin Kim, Jonathon A. Leipsic, Erica Maffei, Hugo Marques, Pedro de Araújo Gonçalves, Gianluca Pontone, Gilbert L. Raff, Ronen Rubinshtein, Todd C. Villines, Heidi Gransar, Erica C. Jones, Jessica M. Peña, Leslee J. Shaw, James K. Min, Jeroen J. Bax

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Aims: We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores – which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) – and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DM patients, because of numerous confounders. Methods: Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabetic patients with suspected CAD who were clinically referred for CCTA. A total of 732 DM patients was 1:1 propensity-matched with 732 non-DM patients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability. Results: A total of 1,464 DM and non-DM patients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DM patients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DM patients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA risk score in DM patients was significantly better than any stenosis ≥50% and ≥70% (p = 0.003 and p = 0.007, respectively), but comparable to the CAD-RADS, SIS, SSS and CT-LeSc that also focus on the extent of CAD (p ≥ 0.265). Conclusion: Coronary atherosclerosis scoring with semiquantitative CCTA risk scores incorporating the total extent of CAD discriminate major adverse cardiac events well, and might be useful for risk stratification of patients with DM beyond the binary evaluation of obstructive stenosis alone.

Original languageEnglish
Pages (from-to)251-257
Number of pages7
JournalJournal of Cardiovascular Computed Tomography
Volume14
Issue number3
DOIs
Publication statusPublished - 2020 May 1

Bibliographical note

Funding Information:
The research reported in this publication was funded, in part, by the National Institute of Health (Bethesda, MD, USA) under award number R01 HL115150. This research was also supported, in part, by the Dalio Institute of Cardiovascular Imaging (New York, NY, USA) and the Michael Wolk Foundation (New York, NY, USA).Dr. James K. Min receives funding from the Dalio Foundation, National Institutes of Health, and GE Healthcare. Dr. Min serves on the scientific advisory board of Arineta and GE Healthcare, and has an equity interest in Cleerly. The Department of Cardiology of the Leiden University Medical Center received research grants from Biotronik, Medtronic, Boston Scientific and Edwards Lifesciences. Arthur J.H.A. Scholte received consulting fees from GE Healthcare and Canon.

Funding Information:
The research reported in this publication was funded, in part, by the National Institute of Health (Bethesda, MD, USA) under award number R01 HL115150 . This research was also supported, in part, by the Dalio Institute of Cardiovascular Imaging (New York, NY, USA) and the Michael Wolk Foundation (New York, NY, USA).

Publisher Copyright:
© 2020 Society of Cardiovascular Computed Tomography

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Cardiology and Cardiovascular Medicine

Fingerprint

Dive into the research topics of 'Coronary atherosclerosis scoring with semiquantitative CCTA risk scores for prediction of major adverse cardiac events: Propensity score-based analysis of diabetic and non-diabetic patients'. Together they form a unique fingerprint.

Cite this