Skip to main content

Advertisement

SpringerLink
Log in

Prognostic value of CT-derived coronary artery disease characteristics varies by ASCVD risk: insights from the PROMISE trial

  • Cardiac
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To compare the prognostic value of individual CT-derived coronary artery disease (CAD) characteristics across categories of clinical cardiovascular risk.

Methods

The central core laboratory assessed coronary artery calcium (CAC), obstructive CAD (stenosis ≥ 50%), and high-risk plaque (HRP) in stable outpatients with suspected CAD enrolled in the PROMISE trial. Multivariable Cox regression models (endpoint: unstable angina, nonfatal myocardial infarction, or all-cause mortality; median follow-up: 2 years) were used to compare hazard ratios (HR) of the CT measures between low-borderline (< 7.5%) and moderate-high (≥ 7.5%) atherosclerotic cardiovascular disease (ASCVD) risk based on the pooled cohort equation.

Results

Among 4356 included patients (aged 61 ± 8 years, 52% women), 67% had ASCVD risk ≥ 7.5%. Stratified by ASCVD risk, CAD ≥ 50% had nearly threefold greater HR in individuals with ASCVD < 7.5% (aHR, 6.85; 95% CI, 2.33–20.15; p < 0.001) vs. ASCVD ≥ 7.5% (aHR: 2.66, 95% CI: 1.67–4.25, p < 0.001; interaction p = 0.041). CAC predicted events solely in ASCVD ≥ 7.5% patients (aHR: 1.92, 95% CI: 1.01–3.63, p = 0.045; interaction p = 0.571), while HRP predicted events only in ASCVD < 7.5% (aHR: 3.11, 95% CI: 1.09–8.85, p = 0.034; interaction p = 0.034).

Conclusions

Prognostic values of CT-derived CAD characteristics differ by ASCVD risk categories. While CAD ≥ 50% has the highest prognostic value regardless of ASCVD risk, CAC is prognostic in high and HRP in low ASCVD risk. These findings suggest that CAD ≥ 50% and HRP detection rather than CAC scoring may better risk-stratify symptomatic low-risk patients and thus potentially improve downstream care.

Key Points

• Prognostic value of individual CT-derived CAD characteristics differs by categories of cardiovascular risk.

• Presence of obstructive coronary artery stenosis ≥ 50% has the highest prognostic value regardless of cardiovascular risk.

• Coronary artery calcium is independently prognostic in high and high-risk plaque features in low cardiovascular risk.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Data Availability

This study is a substudy of the PROMISE trial, which was sponosored by the NIH. Therefore, the data of the partent trial will be made available in the future according to NIH guidelines.

Abbreviations

ACC/AHA:

American College of Cardiology/American Heart Association

ASCVD:

Atherosclerotic cardiovascular disease

CAC:

Coronary artery calcium

CAD:

Coronary artery disease

CI:

Confidence interval

CT:

Computed tomography

ESC:

European Society of Cardiology

HDL:

High-density lipoprotein

HR:

Hazard ratio

HRP:

High-risk plaque

LDL:

Low-density lipoprotein

PROMISE:

Prospective Multicenter Imaging Study for Evaluation of Chest Pain

SCOT-HEART:

Scottish Computed Tomography of the Heart

References

  1. Douglas PS, Hoffmann U, Patel MR et al (2015) Outcomes of anatomical versus functional testing for coronary artery disease. N Engl J Med 372:1291–1300. https://doi.org/10.1056/NEJMoa1415516

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. SCOT-HEART Investigators, Newby DE, Adamson PD et al (2018) Coronary CT Angiography and 5-year risk of myocardial infarction. N Engl J Med 379:924–933. https://doi.org/10.1056/NEJMoa1805971

  3. SCOT-HEART investigators (2015) CT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label, parallel-group, multicentre trial. Lancet 385:2383–2391. https://doi.org/10.1016/S0140-6736(15)60291-4

    Article  Google Scholar 

  4. (2022) CT or invasive coronary angiography in stable chest pain. N Engl J Med 0:null. https://doi.org/10.1056/NEJMoa2200963

  5. Knuuti J, Wijns W, Saraste A et al (2019) ESC Guidelines for the diagnosis and management of chronic coronary syndromesThe Task Force for the diagnosis and management of chronic coronary syndromes of the European Society of Cardiology (ESC). Eur Heart J. https://doi.org/10.1093/eurheartj/ehz425

    Article  PubMed  Google Scholar 

  6. Gulati M, Levy PD, Mukherjee D et al (2021) 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR guideline for the evaluation and diagnosis of chest pain: a report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines. J Cardiovasc Comput Tomogr. https://doi.org/10.1016/j.jcct.2021.11.009

    Article  PubMed  Google Scholar 

  7. Goff DC, Lloyd-Jones DM, Bennett G et al (2014) 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 63:2935–2959. https://doi.org/10.1016/j.jacc.2013.11.005

    Article  PubMed  Google Scholar 

  8. Grundy SM, Stone NJ, Bailey AL, et al (2018) 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol 25709. https://doi.org/10.1016/j.jacc.2018.11.003

  9. Detrano R, Guerci AD, Carr JJ et al (2008) Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med 358:1336–1345. https://doi.org/10.1056/NEJMoa072100

    Article  CAS  PubMed  Google Scholar 

  10. Budoff MJ, Thomas M, Maros F et al (2017) Prognostic value of coronary artery calcium in the PROMISE study (Prospective Multicenter Imaging Study for Evaluation of Chest Pain). Circulation 136:1993–2005. https://doi.org/10.1161/CIRCULATIONAHA.117.030578

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Hoffmann U, Massaro JM, D’Agostino RB, et al (2016) Cardiovascular event prediction and risk reclassification by coronary, aortic, and valvular calcification in the Framingham Heart Study. J Am Heart Assoc 5:. https://doi.org/10.1161/JAHA.115.003144

  12. Bittencourt MS, Hulten E, Ghoshhajra B et al (2014) Prognostic value of nonobstructive and obstructive coronary artery disease detected by coronary computed tomography angiography to identify cardiovascular events. Circ Cardiovasc Imaging 7:282–291. https://doi.org/10.1161/CIRCIMAGING.113.001047

    Article  PubMed  Google Scholar 

  13. Bittner DO, Thomas M, Matt B et al (2020) Prognostic value of coronary CTA in stable chest pain. JACC Cardiovasc Imaging 13:1534–1545. https://doi.org/10.1016/j.jcmg.2019.09.012

    Article  PubMed  Google Scholar 

  14. Hoffmann U, Ferencik M, Udelson JE et al (2017) Prognostic value of noninvasive cardiovascular testing in patients with stable chest pain: insights from the promise trial (prospective multicenter imaging study for evaluation of chest pain). Circulation. https://doi.org/10.1161/CIRCULATIONAHA.116.024360

  15. Ferencik M, Mayrhofer T, Bittner DO et al (2018) Use of high-risk coronary atherosclerotic plaque detection for risk stratification of patients with stable chest pain: a secondary analysis of the PROMISE randomized clinical trial. JAMA Cardiol. https://doi.org/10.1001/jamacardio.2017.4973

    Article  PubMed  PubMed Central  Google Scholar 

  16. Feuchtner G, Kerber J, Burghard P et al (2017) The high-risk criteria low-attenuation plaque <60 HU and the napkin-ring sign are the most powerful predictors of MACE: a long-term follow-up study. Eur Heart J Cardiovasc Imaging 18:772–779. https://doi.org/10.1093/ehjci/jew167

    Article  PubMed  Google Scholar 

  17. Douglas PS, Hoffmann U, Lee KL et al (2014) PROspective Multicenter Imaging Study for Evaluation of chest pain: rationale and design of the PROMISE trial. Am Heart J 167:796-803.e1. https://doi.org/10.1016/j.ahj.2014.03.003

    Article  PubMed  PubMed Central  Google Scholar 

  18. Agatston AS, Janowitz WR, Hildner FJ et al (1990) Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol 15:827–832

    Article  CAS  PubMed  Google Scholar 

  19. Hansson GK (2005) Inflammation, atherosclerosis, and coronary artery disease. N Engl J Med 352:1685–1695. https://doi.org/10.1056/NEJMra043430

    Article  CAS  PubMed  Google Scholar 

  20. Aditya G, Dey AK, Abhishek C et al (2020) Chronic stress-related neural activity associates with subclinical cardiovascular disease in psoriasis. JACC Cardiovasc Imaging 13:465–477. https://doi.org/10.1016/j.jcmg.2018.08.038

    Article  Google Scholar 

  21. Hansildaar R, Vedder D, Baniaamam M et al (2021) Cardiovascular risk in inflammatory arthritis: rheumatoid arthritis and gout. Lancet Rheumatol 3:e58–e70. https://doi.org/10.1016/S2665-9913(20)30221-6

    Article  CAS  PubMed  Google Scholar 

  22. Subramanian S, Tawakol A, Burdo TH et al (2012) Arterial inflammation in patients with HIV. JAMA 308:379–386. https://doi.org/10.1001/jama.2012.6698

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Osborne MT, Shin LM, Mehta NN et al (2020) Disentangling the links between psychosocial stress and cardiovascular disease. Circ Cardiovasc Imaging 13:e010931. https://doi.org/10.1161/CIRCIMAGING.120.010931

    Article  PubMed  PubMed Central  Google Scholar 

  24. Ahmed T, Osborne MT, Ying W et al (2019) Stress-associated neurobiological pathway linking socioeconomic disparities to cardiovascular disease. J Am Coll Cardiol 73:3243–3255. https://doi.org/10.1016/j.jacc.2019.04.042

    Article  Google Scholar 

  25. Delfino RJ, Staimer N, Tjoa T et al (2008) Circulating biomarkers of inflammation, antioxidant activity, and platelet activation are associated with primary combustion aerosols in subjects with coronary artery disease. Environ Health Perspect 116:898–906. https://doi.org/10.1289/ehp.11189

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Delfino RJ, Tjoa T, Gillen DL, et al (2010) Traffic-related air pollution and blood pressure in elderly subjects with coronary artery disease. Epidemiol Camb Mass 21:https://doi.org/10.1097/EDE.0b013e3181d5e19b

  27. Osborne MT, Radfar A, Hassan MZO et al (2020) A neurobiological mechanism linking transportation noise to cardiovascular disease in humans. Eur Heart J 41:772–782. https://doi.org/10.1093/eurheartj/ehz820

    Article  PubMed  Google Scholar 

  28. Budoff MJ, Young R, Burke G et al (2018) Ten-year association of coronary artery calcium with atherosclerotic cardiovascular disease (ASCVD) events: the multi-ethnic study of atherosclerosis (MESA). Eur Heart J 39:2401–2408. https://doi.org/10.1093/eurheartj/ehy217

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Pursnani A, Chou E, Zakroysky P et al (2015) Utility of coronary artery calcium scanning beyond coronary CT angiography in the emergency department evaluation for acute chest pain: The ROMICAT II Trial. Circ Cardiovasc Imaging 8:e002225. https://doi.org/10.1161/CIRCIMAGING.114.002225

    Article  PubMed  PubMed Central  Google Scholar 

  30. Hoffmann U, Massaro JM, Fox CS et al (2008) Defining normal distributions of coronary artery calcium in women and men (from the Framingham Heart Study). Am J Cardiol 102:1136-1141.e1. https://doi.org/10.1016/j.amjcard.2008.06.038

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Yeboah J, Young R, McClelland RL et al (2016) Utility of nontraditional risk markers in atherosclerotic cardiovascular disease risk assessment. J Am Coll Cardiol 67:139–147. https://doi.org/10.1016/j.jacc.2015.10.058

    Article  PubMed  PubMed Central  Google Scholar 

  32. Pál M-H, Schlett CL, Hatem A et al (2012) The napkin-ring sign indicates advanced atherosclerotic lesions in coronary CT angiography. JACC Cardiovasc Imaging 5:1243–1252. https://doi.org/10.1016/j.jcmg.2012.03.019

    Article  Google Scholar 

  33. Ladapo JA, Hoffmann U, Lee KL, et al Changes in medical therapy and lifestyle after anatomical or functional testing for coronary artery disease. J Am Heart Assoc 5:e003807. https://doi.org/10.1161/JAHA.116.003807

Download references

Funding

The current work was supported by the following PROMISE grants: R01HL098237, R01HL098236, R01HL098305, and R01HL098235.

Author information

Authors and Affiliations

  1. Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge Street, Suite 400, Boston, MA, 02114, USA

    Borek Foldyna, Thomas Mayrhofer, Michael T. Lu, Júlia Karády & Márton Kolossváry

  2. School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany

    Thomas Mayrhofer

  3. Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary

    Júlia Karády

  4. Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA

    Maros Ferencik

  5. Duke Clinical Research Institute, Duke University School of Medicine, Durham, NC, USA

    Svati H. Shah, Neha J. Pagidipati & Pamela S. Douglas

  6. Innovative Imaging Consulting LLC, 163 Longfellow Rd, Waltham, MA, 02453, USA

    Udo Hoffmann

Authors
  1. Borek Foldyna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thomas Mayrhofer
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Michael T. Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Júlia Karády
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Márton Kolossváry
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Maros Ferencik
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Svati H. Shah
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Neha J. Pagidipati
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Pamela S. Douglas
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Udo Hoffmann
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Borek Foldyna or Udo Hoffmann.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Dr. Borek Foldyna.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (Prof. Thomas Mayrhofer) has significant statistical expertise, and no complex statistical methods were necessary for this paper.

Informed consent

Local and central institutional review boards approved the study; informed consent was waived.

Ethical approval

Local and central institutional review boards approved the study.

Methodology

• Sub-analysis of a randomized controlled trial.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 67 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Foldyna, B., Mayrhofer, T., Lu, M.T. et al. Prognostic value of CT-derived coronary artery disease characteristics varies by ASCVD risk: insights from the PROMISE trial. Eur Radiol 33, 4657–4667 (2023). https://doi.org/10.1007/s00330-023-09430-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-023-09430-5

Keywords

Search

Navigation