CCTA, CACS and ECG Stress Testing in Patients With Suspected CAD: Precision Phenotyping and Financial Evaluation

NCT ID: NCT04424121

Last Updated: 2020-09-14

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

900 participants

Study Classification

INTERVENTIONAL

Study Start Date

2021-01-01

Study Completion Date

2023-12-31

Brief Summary

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The "DATASET-PRECISE", a 3-arm parallel randomized study, aims to provide new insights in risk stratification of patients with suspected CAD in the Greek population. The convergence of information derived from exercise ECG stress test, CACS, CCTA and metabolomic profiling in artificial intelligence algorithms describes in brief the main objective of this protocol. The design of the present proposal is based on current state-of-the-art literature, incorporating, however, additional innovative elements. It is about the first randomized study to be conducted in Greece, investigating the role of CCTA and CACS in CAD diagnosis and risk assessment. Moreover, the present protocol aims to integrate information on patients' metabolomic profiling. The process of the whole information by using artificial intelligence technology will lead to the development of new risk stratification algorithms, promoting further personalized diagnostic and therapeutic approach. Regarding Greece, this is the first prospectively enrolling medical database of this scale.

Detailed Description

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Symptom-based pre-test probability (PTP) scores that estimate the likelihood of obstructive CAD in stable chest pain have moderate accuracy. Appreciating and integrating the myriad risk predictors in an individual patient is a challenge for the clinician. To date, efforts to improve risk-stratification by using CCTA have largely relied upon luminal stenosis severity. The emphasis placed on this variable over others is in alignment with prior studies using invasive coronary angiography but ignores an array of other parameters important in the CAD pathogenic process, including coronary artery geometry, coronary calcium content, plaque composition, and plaque burden. As an increasing number of CCTA variables along with all clinical and metabolomic variables affecting risk need to be considered, the complexity of assessment increases, making it more difficult for a clinician to draw an overall conclusion regarding risk in an individual patient. Furthermore, the potential influence of unexpected interactions between several weaker predictors in an individual patient is often overlooked. In this study, we are seeking to develop an Artificial Intelligence (AI)-based model, utilizing clinical and metabolomic risk factors, serum biomarkers, CCTA imaging biomarkers, coronary artery calcium score and ECG stress testing variables, to predict the presence and the complexity of CAD. Moreover, we are trying to introduce an easy to use, cost-effective, clinical decision supporting tool. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream personalized management. Briefly, the research objectives of the study are: 1. predict the risk of obstructive coronary artery disease, 2. quantify the burden and complexity of coronary atherosclerosis, 3. evaluate the prognostic risk in individual patients with suspected CAD, 4. provide more accurate diagnosis and risk stratification, 5. provide an easy to use, cost-effective clinical decision support tool, 6. improve decisions in low to intermediate risk patients regarding the need for further testing such as cardiac SPECT and invasive coronary angiography, as well as for the need for preventive therapies and finally, compare three diagnostic strategies in patients with suspected CAD in terms of efficacy and cost-effectiveness.

The "DATASET-PRECISE" is a prospective, multi-center, open-label, 3-arm parallel randomized study. Following clinical consultation, participants will be approached and randomized 1:1:1 to receive standard care plus ECG-stress testing or standard care plus ECG-stress testing and CACS or standard care plus ≥ 64-multidetector CCTA and CACS (Collaborating Organizations: 1st Cardiology Department of AUTH, 1st Cardiology Department of NKUA, Lefkos Stavros-The Athens Clinic \& Affidea Kozani Cardiac Imaging Center). Randomization will be conducted using a web-based system to ensure allocation concealment. The trial will enroll consecutive patients with stable symptoms and suspected CAD admitted to study clinical sites over a period of 12 months. Patients with a previous history of CAD and/or prior revascularization will be excluded. Subjects will undergo screening during the first day of examination, a 5ml blood sample will be collected one minute prior examination for metabolomic analysis (collaboration with the Lab. of Bioanalysis \& Toxicology, School of Medicine, AUTH) and will be followed for 18 months afterwards. The overall recruitment period is expected to last 12 months. The estimated total duration of the study from first patient screened to last patient last visit is 30 months.

Based on previous studies for 80% power at a two-sided P value of 0.05, we will need to recruit about 250 patients per group to detect a relative reduction in the combined MACE rate (cardiac death, non-fatal myocardial infarction, revascularization or chest-pain rehospitalization) of 10% in the CCTA arm. A sample size of N = 900 patients is a pragmatic approach for such a first clinical study in the Greek population. Health service costs will be assigned to the type and intensity of resource use, measured by the number of diagnostic and therapeutic procedures or interventions, medications, hospital clinic attendances and hospitalization episodes from randomization to 18 months of follow-up. Costs will be attributed to the need for: 1. additional invasive or noninvasive imaging, 2. drug therapy, 3. coronary revascularization and 4. hospitalization for chest pain.

Conditions

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Stable Angina Coronary Artery Disease Atherosclerosis Coronary Artery Calcification

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Open-label, 3-arm parallel randomized study
Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

NONE

Open-label, 3-arm parallel randomized study

Study Groups

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Standard of care plus ECG Stress Testing

Participants will be approached and randomized to receive standard care plus ECG-stress testing

Group Type NO_INTERVENTION

No interventions assigned to this group

Standard of care plus ECG Stress Testing and CACS

Participants will be approached and randomized to receive standard care plus ECG-stress testing and coronary artery calcium scoring

Group Type NO_INTERVENTION

No interventions assigned to this group

Standard of care plus CCTA

Participants will be approached and randomized to receive standard care plus ≥ 64 multidetector coronary computed tomography angiography

Group Type ACTIVE_COMPARATOR

CCTA

Intervention Type DIAGNOSTIC_TEST

Coronary Computed Tomography Angiography

Interventions

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CCTA

Coronary Computed Tomography Angiography

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

1. Patients with stable symptoms and low to intermediate probability of coronary artery disease (CAD) referred for evaluation
2. Patients without known history of CAD
3. Patients older than 18 years
4. Patients giving voluntary written consent to participate in the study
5. Subject is willing to comply with study follow-up requirements

Exclusion Criteria

1. Patients with a previous history of CAD
2. Patients who refuse to give written consent for participation in the study
3. In the investigator's opinion, subject will not be able to comply with the follow-up requirements
4. Known pregnancy
5. Subject has a known allergy to contrast agent that cannot be adequately pre-medicated
6. Inability or unwilling to undergo computed tomography scanning, such as exceeding weight tolerance of scanner
7. Severe renal failure (estimated Glomerular Filtration Rate-eGFR \<30 mL/min)
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Lefkos Stavros The Athens Clinic

UNKNOWN

Sponsor Role collaborator

National and Kapodistrian University of Athens

OTHER

Sponsor Role collaborator

Aristotle University Of Thessaloniki

OTHER

Sponsor Role lead

Responsible Party

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Georgios P Rampidis, MD, MSc

Academic Scholar

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Haralambos Karvounis, Prof. in Cardiology

Role: STUDY_CHAIR

Aristotle University Of Thessaloniki

Georgios Giannakoulas, Prof. in Cardiology

Role: STUDY_DIRECTOR

Aristotle University Of Thessaloniki

Periklis Kounatiadis, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

Aristotle University Of Thessaloniki

Panagiotis Bamidis, Prof. in Bioinformatics

Role: PRINCIPAL_INVESTIGATOR

Aristotle University Of Thessaloniki

Georgios Rampidis, MD, MSc

Role: PRINCIPAL_INVESTIGATOR

Aristotle University Of Thessaloniki

Olga Deda, PhD

Role: PRINCIPAL_INVESTIGATOR

Aristotle University Of Thessaloniki

Antonios Billis, PhD

Role: PRINCIPAL_INVESTIGATOR

Aristotle University Of Thessaloniki

Locations

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Lefkos Stavros The Athens Clinic

Athens, , Greece

Site Status

National and Kapodistrian University of Athens, School of Medicine

Athens, , Greece

Site Status

Aristotle University of Thessaloniki, School of Medicine

Thessaloniki, , Greece

Site Status

Countries

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Greece

Central Contacts

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Georgios Rampidis, MD, MSc

Role: CONTACT

2310994830 ext. +30

Facility Contacts

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Georgios Benetos, MD, PhD

Role: primary

Georgios Benetos, MD, PhD

Role: primary

Georgios Rampidis, MD, MSc

Role: primary

References

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Benz DC, Benetos G, Rampidis G, von Felten E, Bakula A, Sustar A, Kudura K, Messerli M, Fuchs TA, Gebhard C, Pazhenkottil AP, Kaufmann PA, Buechel RR. Validation of deep-learning image reconstruction for coronary computed tomography angiography: Impact on noise, image quality and diagnostic accuracy. J Cardiovasc Comput Tomogr. 2020 Sep-Oct;14(5):444-451. doi: 10.1016/j.jcct.2020.01.002. Epub 2020 Jan 13.

Reference Type BACKGROUND
PMID: 31974008 (View on PubMed)

Benetos G, Buechel RR, Goncalves M, Benz DC, von Felten E, Rampidis GP, Clerc OF, Messerli M, Giannopoulos AA, Gebhard C, Fuchs TA, Pazhenkottil AP, Kaufmann PA, Grani C. Coronary artery volume index: a novel CCTA-derived predictor for cardiovascular events. Int J Cardiovasc Imaging. 2020 Apr;36(4):713-722. doi: 10.1007/s10554-019-01750-2. Epub 2020 Jan 1.

Reference Type BACKGROUND
PMID: 31894527 (View on PubMed)

Rampidis GP, Benetos G, Benz DC, Giannopoulos AA, Buechel RR. A guide for Gensini Score calculation. Atherosclerosis. 2019 Aug;287:181-183. doi: 10.1016/j.atherosclerosis.2019.05.012. Epub 2019 May 10. No abstract available.

Reference Type BACKGROUND
PMID: 31104809 (View on PubMed)

Knuuti J, Wijns W, Saraste A, Capodanno D, Barbato E, Funck-Brentano C, Prescott E, Storey RF, Deaton C, Cuisset T, Agewall S, Dickstein K, Edvardsen T, Escaned J, Gersh BJ, Svitil P, Gilard M, Hasdai D, Hatala R, Mahfoud F, Masip J, Muneretto C, Valgimigli M, Achenbach S, Bax JJ; ESC Scientific Document Group. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes. Eur Heart J. 2020 Jan 14;41(3):407-477. doi: 10.1093/eurheartj/ehz425. No abstract available.

Reference Type BACKGROUND
PMID: 31504439 (View on PubMed)

Budoff MJ, Mayrhofer T, Ferencik M, Bittner D, Lee KL, Lu MT, Coles A, Jang J, Krishnam M, Douglas PS, Hoffmann U; PROMISE Investigators. Prognostic Value of Coronary Artery Calcium in the PROMISE Study (Prospective Multicenter Imaging Study for Evaluation of Chest Pain). Circulation. 2017 Nov 21;136(21):1993-2005. doi: 10.1161/CIRCULATIONAHA.117.030578. Epub 2017 Aug 28.

Reference Type BACKGROUND
PMID: 28847895 (View on PubMed)

SCOT-HEART Investigators; Newby DE, Adamson PD, Berry C, Boon NA, Dweck MR, Flather M, Forbes J, Hunter A, Lewis S, MacLean S, Mills NL, Norrie J, Roditi G, Shah ASV, Timmis AD, van Beek EJR, Williams MC. Coronary CT Angiography and 5-Year Risk of Myocardial Infarction. N Engl J Med. 2018 Sep 6;379(10):924-933. doi: 10.1056/NEJMoa1805971. Epub 2018 Aug 25.

Reference Type BACKGROUND
PMID: 30145934 (View on PubMed)

Hilvo M, Meikle PJ, Pedersen ER, Tell GS, Dhar I, Brenner H, Schottker B, Laaperi M, Kauhanen D, Koistinen KM, Jylha A, Huynh K, Mellett NA, Tonkin AM, Sullivan DR, Simes J, Nestel P, Koenig W, Rothenbacher D, Nygard O, Laaksonen R. Development and validation of a ceramide- and phospholipid-based cardiovascular risk estimation score for coronary artery disease patients. Eur Heart J. 2020 Jan 14;41(3):371-380. doi: 10.1093/eurheartj/ehz387.

Reference Type BACKGROUND
PMID: 31209498 (View on PubMed)

von Felten E, Messerli M, Giannopoulos AA, Benz DC, Schwyzer M, Benetos G, Rampidis G, Patriki D, Kamani CH, Grani C, Fuchs TA, Pazhenkottil AP, Gebhard C, Kaufmann PA, Buechel RR. Potential of Radiation Dose Reduction by Optimizing Z-Axis Coverage in Coronary Computed Tomography Angiography on a Latest-Generation 256-Slice Scanner. J Comput Assist Tomogr. 2020 Mar/Apr;44(2):289-294. doi: 10.1097/RCT.0000000000000993.

Reference Type BACKGROUND
PMID: 32195809 (View on PubMed)

Other Identifiers

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DATASET PRECISE_01062020_03448

Identifier Type: -

Identifier Source: org_study_id

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