Rapid Engagement for Solutions to Population and Outcomes Through Networked Dialogue for Coronary Heart Disease
NCT ID: NCT07260552
Last Updated: 2025-12-10
Study Results
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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NOT_YET_RECRUITING
200 participants
OBSERVATIONAL
2027-02-01
2030-09-01
Brief Summary
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Detailed Description
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The study team will conduct a pragmatic randomized, controlled trial at two sites (rural versus urban). At each site the team will enroll 100 adults aged 40-69 years without known CHD and who are not on a statin. The 10-yr risk of CHD will be estimated based on pooled cohort equations (PCE). Participants will view a video describing how cardiovascular risk was estimated and how lifestyle changes and drug therapy could reduce such risk and, in those randomized to receive PRS, the probabilistic nature of genetic risk. DNA will be obtained from saliva/blood and a PRS for CHD will be calculated in a CLIA-certified laboratory, using the global diversity array. Patients will then see their PCP to review the 10-yr CHD risk estimate and engage in shared decision-making regarding statin therapy. The study team will assess patient and clinician understanding of polygenic risk information, as well as health-related and behavioral outcomes.
Visit #1: In individuals who have consented for the study, height, weight, and blood pressure will be measured by the study coordinator at the baseline study visit. Demographic information, medication history, and family history (details above) will be collected. A 5ml blood draw will be performed by a trained individual for both a lipid panel and for genotyping. Participant fills out surveys for baseline qualitative assessments. (e.g. numeracy, genetic literacy, perceived heart disease risk, perceived personal control, intention to change, anxiety, impact of events, genetic determinism of understanding PRS results, smoking status, dietary fat, physical activity level, concerns about placing PRS in the HER, intent to pursue medical assistance or counseling in response to PRS, views regarding sharing results with family members, worries about future employability or insurance coverage)
Visit #2: Participants will return after 2 months to be randomized to disclosure of risk estimate based on conventional risk score (CRS) versus an integrated risk score (IRS). The study coordinator will disclose the 10-yr coronary heart disease risk and walk the subject through a 10 minute educational video. This will be followed by a visit with the primary care physician/provider. The patient and provider will then engage in shared decision-making regarding statin initiation. Participant fills out surveys to assess post-disclosure qualitative assessments. (e.g. perceived heart disease risk, perceived personal control, intention to change, impact of events, genetic determinism understanding PRS results, smoking status, dietary fat, physical activity, communication of results, comprehension of results, shared decision-making satisfaction, knowledge transfer, decisional conflict, recall, decisional regret, concerns about placing PRS in the HER, intent to pursue medical assistance or counseling in response to PRS, views regarding sharing results with family members, worries about future employability or insurance coverage)
Physician outcomes. A post-visit questionnaire will assess physicians' satisfaction with the risk communication tool and the decision-making process. The study team will address any bias related to interpretation of PRS. The survey will be completed immediately following the patient visit.
The discriminant ability of multivariable risk prediction equations for cardiometabolic diseases remains modest due to lack of sufficiently predictive biomarkers. Polygenic risk scores (PRSs) provide orthogonal risk information, thereby improving accuracy of risk prediction equations. The potential utility of PRS to increase accuracy of risk prediction and improve outcomes has been highlighted in multiple reports but has not been studied in low resource rural and inner-city settings. While there is optimism that PRS will empower patients to improve their health through preventive practices and early interventions, there is concern that the understanding that PRS tests offering probabilistic estimates for risks of common diseases among both the lay public and medical professionals is poor.
Study Procedures Study sites: The study will be conducted at two sites: The Outreach Community Health Center (OCHC) Primary Care clinic in Milwaukee and ThedaCare Medical Center (TCMC) - Shawano. OCHC - Milwaukee is a federally qualified health center that provides \>8,000 primary care visits annually for adult (\>18 years) patients. TCMC - Shawano provides approximately 12,000 to 15,000 primary care encounters on an annual basis.
Genotyping: Genotyping will be conducted in the Broad CLIA certified and CAP-accredited laboratory on the Global Diversity Array that includes \~1.8M SNPs and imputes over 25,000,000 SNPs. Broad's genotyping services for research include sample collection kits, arrays, reagents, DNA extraction, data processing, and a custom online dashboard to track study samples, manage enrollment, and access data. The dashboard tracks participants enrolled, percentage of kits received, progress of samples, and PRS results.
Baseline measures: The study team will obtain information about demographic factors including self-identified race and ethnicity (SIRE), personal medical history, social history, family history, educational attainment, home address-derived socioeconomic status and environmental information, social determinants of health (SDOH), primary language, and insurance status (i.e., commercial, Medicare, uninsured) from EHR and survey data. Participants will complete baseline surveys that assess smoking status, diet, physical activity, and perception of disease risk, conventional risk factors, and family history86,87. Height, weight, and BP will be measured by the study coordinator at the baseline study visit. Study data will be placed in a REDCap database105,106.
Family history: Family history is a valuable genomic tool107 and provides important contextual background for returning PRS. The study team will use a family history tool currently being used in the eMERGE phase IV study.94 Family history of early CHD will be defined as occurrence of a CHD event in a first-degree male relative before age 55 years or in a first degree female relative before age 65 years.
Calculation of a PRS: The study team will calculate a genome-wide PRS for CHD for each participant according to a weighted sum of their single nucleotide variant (SNV) genotypes, where each genotype codes the dose of the minor allele for a SNV, and the weights represent the effect size (log-odds-ratios) of the SNV on the phenotype. The investigative team will use the most current and best performing multi-ancestry PRSs that is portable to different ancestry groups.
Return of Results: Once results are ready, letter requesting that the participant set up an appointment with a study coordinator who will summarize results and lead the participant through a 10-min video about disease risk factors and potential means for risk reduction will be sent. A conventional risk score (CRS) for CHD will be calculated using the Pooled Cohort Equations (PCE). An Integrated Risk Score (IRS) will be computed by combining PRS with PCE. Clinical data will be extracted, normalized, and placed in REDCap. An appointment with a genetic counselor will be available to those participants who request it.
Randomization: Participants will be randomized to disclosure of risk based on CRS alone vs IRS, prior to their PCP visit. To ensure allocation concealment, the study coordinator will consult a central randomization line set up by the study statistician to randomize patients (1:1) to the two arms, one group receiving IRS derived by incorporating PRS into PCE, and the other (n= 100) CRS alone based on PCE. Participants will be randomized using a permuted block algorithm (block size 8), balancing age and sex in both arms. Blinding. Patients and clinicians will be aware that PRS may alter estimates of risk. Data analysts will be blinded to allocation. Intention-to-treat principle. Resources will be set aside to follow all patients to study completion and analyze them primarily as randomized. Fidelity. Participating clinicians will receive formal training in the use of a genomic decision-aid that incorporates the genotype-informed estimate of risk. This training will be performed by study investigators and mock sessions conducted so that they are fully familiar with the tool and the standard language to disclose risk.
Statistical Methods to analyze differences in primary and secondary endpoints between the two study groups. Initial evaluations of the data will include inspection of the raw data, descriptive statistics, examination of outliers and group distributions, and evaluation of missing data. Standard techniques will be used that are appropriate for patient randomized trials, with each outcome compared between study arms using t-tests for continuous outcomes and chi-square tests for dichotomous outcomes. If there are differences in baseline characteristics between the two study groups, these will be accounted for, using regression models which include an indicator for study arm. Exploratory analyses will be conducted to assess a) whether the presence of family history of CHD influences the study outcomes and b) whether outcomes differ by site (rural vs. urban).
Sample size and power calculations. Sample size was based on aiming for 90% power to detect an absolute difference in statin initiation from 20% in control arm to 40% in the intervention arm (PRS disclosure) at two-sided α = 0.05 using the normal-approximation formula for two independent proportions. The expected frequency of statin initiation is based on data from our prior MIGENES clinical trial.48 Even accounting for 15-20% loss to follow-up or missing outcome data, the study will have \~80% power to detect an absolute difference in statin initiation from 20% to 40%.
9\. Potential Risks/ Risk Mitigation
1. Blood Draw: at baseline and after 2-3 months of result disclosure.
2. Loss of Confidentiality: Each participant will be assigned a code and the data will be filed according to code. Subject identity will be known only to the PIs and necessary research personnel. The information, including the consent forms, will be maintained in a location that is approved by the IRB.
Conditions
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Study Design
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OTHER
PROSPECTIVE
Study Groups
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Adults aged 40-69 years
Adults aged 40-69 years without known coronary heart disease and who are not currently prescribed a statin medication.
Polygenic risk score
The polygenic risk score is a precision medicine screening tool to determine one's future risk of coronary heart disease.
Interventions
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Polygenic risk score
The polygenic risk score is a precision medicine screening tool to determine one's future risk of coronary heart disease.
Eligibility Criteria
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Inclusion Criteria
* No prior history of coronary heart disease
* No prior use of statin medication
* Has primary care provider
Exclusion Criteria
* current use of statin medication
40 Years
69 Years
ALL
Yes
Sponsors
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Medical College of Wisconsin
OTHER
Responsible Party
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Central Contacts
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References
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Slunecka JL, van der Zee MD, Beck JJ, Johnson BN, Finnicum CT, Pool R, Hottenga JJ, de Geus EJC, Ehli EA. Implementation and implications for polygenic risk scores in healthcare. Hum Genomics. 2021 Jul 20;15(1):46. doi: 10.1186/s40246-021-00339-y.
Kullo IJ, Jouni H, Austin EE, Brown SA, Kruisselbrink TM, Isseh IN, Haddad RA, Marroush TS, Shameer K, Olson JE, Broeckel U, Green RC, Schaid DJ, Montori VM, Bailey KR. Incorporating a Genetic Risk Score Into Coronary Heart Disease Risk Estimates: Effect on Low-Density Lipoprotein Cholesterol Levels (the MI-GENES Clinical Trial). Circulation. 2016 Mar 22;133(12):1181-8. doi: 10.1161/CIRCULATIONAHA.115.020109. Epub 2016 Feb 25.
Kullo IJ. Promoting equity in polygenic risk assessment through global collaboration. Nat Genet. 2024 Sep;56(9):1780-1787. doi: 10.1038/s41588-024-01843-2. Epub 2024 Aug 5.
Kullo IJ. Clinical use of polygenic risk scores: current status, barriers and future directions. Nat Rev Genet. 2025 Oct 10. doi: 10.1038/s41576-025-00900-8. Online ahead of print.
Kullo IJ, Lewis CM, Inouye M, Martin AR, Ripatti S, Chatterjee N. Polygenic scores in biomedical research. Nat Rev Genet. 2022 Sep;23(9):524-532. doi: 10.1038/s41576-022-00470-z. Epub 2022 Mar 30.
Kullo IJ, Trejo-Gutierrez JF, Lopez-Jimenez F, Thomas RJ, Allison TG, Mulvagh SL, Arruda-Olson AM, Hayes SN, Pollak AW, Kopecky SL, Hurst RT. A perspective on the New American College of Cardiology/American Heart Association guidelines for cardiovascular risk assessment. Mayo Clin Proc. 2014 Sep;89(9):1244-56. doi: 10.1016/j.mayocp.2014.06.018. Epub 2014 Aug 12.
Other Identifiers
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FP00030260
Identifier Type: -
Identifier Source: org_study_id
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