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

Sponsor

Aristotle University Of Thessaloniki (Other)

Overall Status

Not yet recruiting

CT.gov ID

NCT04424121

Collaborator

Lefkos Stavros The Athens Clinic (Other), National and Kapodistrian University of Athens (Other)

900

Enrollment

Locations

Arms

35.9

Anticipated Duration (Months)

300

Patients Per Site

8.3

Patients Per Site Per Month

Study Details

Study Description

Brief Summary

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.

Condition or Disease	Intervention/Treatment	Phase
Stable Angina Coronary Artery Disease Atherosclerosis Coronary Artery Calcification	Diagnostic Test: CCTA	N/A

Detailed Description

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.

Study Design

Study Type:

Interventional

Anticipated Enrollment :

900 participants

Allocation:

Randomized

Intervention Model:

Parallel Assignment

Intervention Model Description:

Open-label, 3-arm parallel randomized studyOpen-label, 3-arm parallel randomized study

Masking:

None (Open Label)

Masking Description:

Open-label, 3-arm parallel randomized study

Primary Purpose:

Diagnostic

Official Title:

Cardiac CT, Calcium Scoring and ECG Stress Testing in Patients With Suspected Coronary Artery Disease: Precision Phenotyping and Financial Evaluation (The DATASET-PRECISE Randomized Trial)

Anticipated Study Start Date :

Jan 1, 2021

Anticipated Primary Completion Date :

Jun 30, 2023

Anticipated Study Completion Date :

Dec 31, 2023

Arms and Interventions

Arm	Intervention/Treatment
No Intervention: Standard of care plus ECG Stress Testing Participants will be approached and randomized to receive standard care plus ECG-stress testing
No Intervention: 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
Active Comparator: Standard of care plus CCTA Participants will be approached and randomized to receive standard care plus ≥ 64 multidetector coronary computed tomography angiography	Diagnostic Test: CCTA Coronary Computed Tomography Angiography

Arm

Intervention/Treatment

No Intervention: Standard of care plus ECG Stress Testing

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

No Intervention: 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

Active Comparator: Standard of care plus CCTA

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

Diagnostic Test: CCTA

Coronary Computed Tomography Angiography

Outcome Measures

Primary Outcome Measures

Major Adverse Cardiac Events (MACE) [18 months]
Defined as cardiac death, non-fatal myocardial infarction or revascularization with percutaneous coronary intervention or coronary artery bypass graft surgery. Revascularization procedures within 6 weeks after the index CCTA will be excluded because they may be triggered by the CCTA findings per se
Chest-pain rehospitalization [18 months]
Frequency (%) of chest-pain rehospitalization

Secondary Outcome Measures

Frequency of angina [Seattle Angina Questionnaire (SAQ)] [6 months]
The SAQ quantifies patients' physical limitations caused by angina, the frequency of and recent changes in their symptoms, their satisfaction with treatment, and the degree to which they perceive their disease to affect their quality of life. Scores range from 0 to 100, where higher scores indicate better function (less physical limitation, less angina and better quality of life)
Frequency of angina [Seattle Angina Questionnaire (SAQ)] [12 months]
The SAQ quantifies patients' physical limitations caused by angina, the frequency of and recent changes in their symptoms, their satisfaction with treatment, and the degree to which they perceive their disease to affect their quality of life. Scores range from 0 to 100, where higher scores indicate better function (less physical limitation, less angina and better quality of life)
Frequency of angina [Seattle Angina Questionnaire (SAQ)] [18 months]
The SAQ quantifies patients' physical limitations caused by angina, the frequency of and recent changes in their symptoms, their satisfaction with treatment, and the degree to which they perceive their disease to affect their quality of life. Scores range from 0 to 100, where higher scores indicate better function (less physical limitation, less angina and better quality of life)
Generic health status [Medical Outcomes Study 12-Item Short Form (SF-12)] [12 months]
The Medical Outcomes Study 12-Item Short Form (SF-12) is a general health questionnaire and is computed using the scores of 12 questions ranging from 0 to 100, where 0 indicates the lowest level of health and 100 indicates the highest level of health

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

Inclusion Criteria:

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

Exclusion Criteria:

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

Contacts and Locations

Locations

	Site	City	Country
1	Lefkos Stavros The Athens Clinic	Athens	Greece
2	National and Kapodistrian University of Athens, School of Medicine	Athens	Greece
3	Aristotle University of Thessaloniki, School of Medicine	Thessaloníki	Greece

Sponsors and Collaborators

Aristotle University Of Thessaloniki
Lefkos Stavros The Athens Clinic
National and Kapodistrian University of Athens

Investigators

Study Chair: Haralambos Karvounis, Prof. in Cardiology, Aristotle University Of Thessaloniki, School of Medicine
Study Director: Georgios Giannakoulas, Prof. in Cardiology, Aristotle University Of Thessaloniki, School of Medicine
Principal Investigator: Periklis Kounatiadis, MD, PhD, Aristotle University Of Thessaloniki, School of Medicine
Principal Investigator: Panagiotis Bamidis, Prof. in Bioinformatics, Aristotle University Of Thessaloniki, School of Medicine
Principal Investigator: Georgios Rampidis, MD, MSc, Aristotle University Of Thessaloniki, School of Medicine
Principal Investigator: Olga Deda, PhD, Aristotle University Of Thessaloniki, School of Medicine
Principal Investigator: Antonios Billis, PhD, Aristotle University Of Thessaloniki, School of Medicine