Personalized Treatment for Coronary Artery Disease

Recruiting at 4 trial locations

Overseen By Joey Freshwater

Age: 18+

Sex: Any

Trial Phase: Academic

Sponsor: Emory University

Disqualifiers: Heart failure, Pregnancy, Malignancy, others

No Placebo Group All trial participants will receive the active study treatment (no placebo)

Compensation: Varies

Number of Visits: 2

Duration: 1 year

450 Participants Needed

What You Need to Know Before You Apply

What is the purpose of this trial?

People with Coronary Artery Disease (CAD) have narrow or blocked arteries that supply blood to the heart. Reduced blood flow to the heart muscle from CAD can cause chest pain or aching, especially with exercise or activity. CAD can lead to weakening of the heart muscle or heart failure, and a higher risk of heart attack or death. Certain proteins in the blood, known as biomarkers, can be found in people with CAD. Higher levels of these biomarkers are associated with a greater risk of complications from CAD. The purpose of this study is to see if a customized treatment based on biomarkers will reduce the biomarker levels and lead to lower risk of complications from CAD.

Will I have to stop taking my current medications?

The trial information does not specify whether you need to stop taking your current medications. It's best to discuss this with the trial coordinators or your doctor.

Is personalized treatment for coronary artery disease safe?

The safety of personalized treatment for coronary artery disease is not directly addressed in the available research articles. However, personalized medicine aims to tailor treatments to individual patients, potentially reducing adverse reactions by considering genetic and other personal factors. ^{1 2 3 4 5}

How is the personalized treatment for coronary artery disease different from other treatments?

This personalized treatment for coronary artery disease uses a patient's unique biological information, such as genetic and clinical data, to tailor therapy specifically for them, unlike standard treatments that follow a one-size-fits-all approach. It leverages machine learning models to predict and improve health outcomes by identifying the best therapy for each individual, potentially extending the time before adverse events occur. ^{1 4 6 7 8}

What data supports the effectiveness of the treatment for coronary artery disease?

Research shows that personalized medicine, which includes tailoring treatments based on individual characteristics like genetics and biomarkers, can improve patient outcomes. Although the cardiovascular field has not widely used genetic markers, using prognostic variables to identify likely responders has been a common practice, suggesting potential benefits for personalized treatment in coronary artery disease. ^{4 5 8 9 10}

Who Is on the Research Team?

Arshed Quyyumi, MD

Principal Investigator

Emory University

Are You a Good Fit for This Trial?

Adults aged 21-90 with stable Coronary Artery Disease (CAD) or those who've had recent heart treatments can join. They must have certain levels of calcium in their arteries or visible atherosclerosis. Excluded are pregnant individuals, those planning heart procedures, severe heart failure patients, transplant recipients, and active cancer patients.

Inclusion Criteria

Your calcium levels in the blood are very high, at 400 or more.

I had heart surgery or a heart attack and it's been weeks since my treatment.

You have blockages in your heart blood vessels shown on a special heart imaging test.

Exclusion Criteria

I was born with a heart condition.

Your heart's pumping function is less than 40%.

I am scheduled for a procedure to restore blood flow.

Timeline for a Trial Participant

Screening

Participants are screened for eligibility to participate in the trial

2-4 weeks

1 visit (in-person)

Treatment

Participants receive customized treatment based on biomarker levels, including medication adjustments and lifestyle changes

1 year

Regular visits for physical exams, blood tests, and questionnaires

Follow-up

Participants are monitored for safety and effectiveness after treatment, including measurements of BRS and adverse events

5 years

Follow-up visits at 1, 3, 6, 9 months and annually up to 5 years

What Are the Treatments Tested in This Trial?

Interventions

• Customized Treatment

Trial Overview The trial is testing if personalized treatment based on blood protein levels (biomarkers) can lower these biomarker levels and reduce complications from CAD. It involves comparing standard care with a tailored medical/behavioral approach guided by the patient's specific biomarker profile.

How Is the Trial Designed?

Group I: Registry Group Experimental Treatment 1 Intervention

Participants with BRS of 0 at baseline and after 3 months will undergo follow-up including measurements of BRS at the time-points specified for the randomized subjects and also for adverse events. Laboratory results and questionnaire data will be obtained on the phone.

Group II: Optimization Group Experimental Treatment 1 Intervention

Participants with CAD and a BRS greater than 0 who are randomized to the Optimization Group have treatment goals that include achieving LDL-C\<70 mg/dL, hemoglobin A1c \<7%, blood pressure \<130/80 mmHg, smoking cessation, at least 30 minutes of moderate-intensity aerobic activity 5 days a week and weight loss to body mass index \<30 kg/m2. To achieve these goals, both pharmacological and lifestyle interventions will be considered and individualized for each patient.

Group III: Usual Care Group Active Control 1 Intervention

Participants with CAD and a BRS greater than 0 who are randomized to the usual care group will receive standard of care therapy prescribed by their primary care physician and/or cardiologist. Patients and their physicians will be informed that their BRS is ≥1 and they have been randomized to the usual care group.

Who Is Running the Clinical Trial?

Emory University

Lead Sponsor

Trials

1,735

Recruited

2,605,000+

Published Research Related to This Trial

Personalized medicine aims to tailor treatments based on individual patient characteristics, including genetic and demographic factors, to improve efficacy and reduce adverse reactions, particularly in cardiovascular disease.

The development of biomarker-based approaches in cardiovascular medicine has been challenging due to the complexity of diseases like heart failure, but better disease classification and understanding of individual variations could lead to more effective targeted therapies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Personalized Cardiovascular Medicine Today: A Food and Drug Administration/Center for Drug Evaluation and Research Perspective. Blaus, A., Madabushi, R., Pacanowski, M., et al.[2019]

Biomarker-guided personalized therapies have the potential to enhance drug development and patient care, but they also create challenges in designing effective clinical trials.

The paper introduces new group sequential designs that can be used to develop and test personalized treatment strategies with approved therapies, aiming to improve the validation process for these innovative approaches.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Group sequential designs for developing and testing biomarker-guided personalized therapies in comparative effectiveness research. Lai, TL., Liao, OY., Kim, DW.[2021]

Advancements in molecular genetics and biology are enabling the identification of numerous biomarkers for cardiovascular diseases, which can help in assessing disease risk, severity, and tailoring individual therapies.

Despite the rapid expansion of potential biomarkers, the field is still developing, and large-scale clinical studies are necessary to confirm their effectiveness in diagnosing and treating cardiovascular conditions.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Biomarkers of cardiac disease. Marian, AJ., Nambi, V.[2015]

Personalized medicine uses an individual's unique biological information to enhance treatment for vascular diseases, but implementing this approach in clinical practice is still challenging.

Recent advancements in pharmacogenomics and vascular biology allow for better customization of four key drug classes in vascular medicine, with ongoing clinical trials needed to compare these personalized strategies against standard treatments.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Personalized vascular medicine: individualizing drug therapy. Degoma, EM., Rivera, G., Lilly, SM., et al.[2022]

Genetic differences among individuals can significantly affect how they respond to medications, influencing both the effectiveness and potential side effects of treatments.

In cardiovascular medicine, pharmacogenomic factors have been linked to important drug responses, such as the risk of thrombosis with clopidogrel and the appropriate dosing of warfarin, highlighting the need for personalized medicine approaches in clinical care.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Applied pharmacogenomics in cardiovascular medicine. Weeke, P., Roden, DM.[2021]

Using electronic health records from 21,460 patients, a new personalized algorithm called ML4CAD was developed, which significantly improves health outcomes for managing Coronary Artery Disease (CAD) by predicting adverse events with an 81.5% accuracy.

The ML4CAD algorithm increases the expected time from diagnosis to adverse events by 24.11%, particularly benefiting male and Hispanic patients, and provides physicians with an interactive tool for personalized treatment recommendations.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Personalized treatment for coronary artery disease patients: a machine learning approach. Bertsimas, D., Orfanoudaki, A., Weiner, RB.[2021]

In a review of 147 clinical trials for cardiovascular disease (CVD), only 1 trial (less than 1%) used a genomic biomarker prospectively to enhance patient selection, despite 32% of drug targets having relevant genetic evidence.

Almost half (46%) of the trials indicated exploratory use of biomarkers, suggesting a significant opportunity to improve drug development efficiency by better integrating genetic knowledge into clinical trial designs.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

An Overview of Genomic Biomarker Use in Cardiovascular Disease Clinical Trials. Adeniyi, O., Ramamoorthy, A., Schuck, R., et al.[2021]

Acute coronary syndromes (ACS) are a major cause of death worldwide, and precision medicine is being used to tailor treatments based on individual patient characteristics, improving outcomes.

Current precision treatments for ACS include immediate coronary revascularization for ST-segment elevation, early coronary angiography for elevated troponins, and personalized antithrombotic therapy based on bleeding risk, highlighting the need for more detailed analyses of patient data to enhance treatment strategies.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Precision Phenomapping of Acute Coronary Syndromes to Improve Patient Outcomes. Andreotti, F., Iervolino, A., Navarese, EP., et al.[2021]

Personalized management of cardiovascular disorders (CVD) utilizes various 'omics' technologies and molecular diagnostics to tailor treatments based on individual patient profiles, improving the effectiveness of interventions.

A systems biology approach helps in risk stratification and treatment modeling, allowing for individualized recommendations that consider genetic and epigenetic factors, ultimately enhancing patient care in conditions like heart failure and hypertension.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Personalized Management of Cardiovascular Disorders. Jain, KK.[2018]

Coronary artery disease (CAD) continues to be the leading cause of death globally, despite advances in prevention and treatment strategies that have reduced cardiovascular mortality.

Personalized medicine, which considers individual patient factors beyond standard clinical presentations, is shown to be more effective than generic treatment approaches, highlighting the importance of tailored risk scoring systems for better clinical decision-making in CAD management.

NCBI (Pubmed)

pubmed.ncbi.nlm.nih.gov

Risk Stratification in Patients with Coronary Artery Disease: A Practical Walkthrough in the Landscape of Prognostic Risk Models. Buccheri, S., D'Arrigo, P., Franchina, G., et al.[2023]

Citations

1. United States pubmed.ncbi.nlm.nih.gov

Personalized Cardiovascular Medicine Today: A Food and Drug Administration/Center for Drug Evaluation and Research Perspective. [2019]

2. United States pubmed.ncbi.nlm.nih.gov

Group sequential designs for developing and testing biomarker-guided personalized therapies in comparative effectiveness research. [2021]

3. England pubmed.ncbi.nlm.nih.gov

Biomarkers of cardiac disease. [2015]

4. England pubmed.ncbi.nlm.nih.gov

Personalized vascular medicine: individualizing drug therapy. [2022]

5. United States pubmed.ncbi.nlm.nih.gov

Applied pharmacogenomics in cardiovascular medicine. [2021]

6. Netherlands pubmed.ncbi.nlm.nih.gov

Personalized treatment for coronary artery disease patients: a machine learning approach. [2021]

7. United States pubmed.ncbi.nlm.nih.gov

An Overview of Genomic Biomarker Use in Cardiovascular Disease Clinical Trials. [2021]

8. Switzerland pubmed.ncbi.nlm.nih.gov

Precision Phenomapping of Acute Coronary Syndromes to Improve Patient Outcomes. [2021]

9. Switzerland pubmed.ncbi.nlm.nih.gov

Personalized Management of Cardiovascular Disorders. [2018]

10. England pubmed.ncbi.nlm.nih.gov

Risk Stratification in Patients with Coronary Artery Disease: A Practical Walkthrough in the Landscape of Prognostic Risk Models. [2023]