Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT03114553 |
| Other study ID # |
Pro00079760 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
July 23, 2017 |
| Est. completion date |
December 2025 |
Study information
| Verified date |
August 2023 |
| Source |
Duke University |
| Contact |
Lori Orlando, MD |
| Phone |
919 660-6606 |
| Email |
lori.orlando[@]duke.edu |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
The purpose of this study is to better understand the linkages between family health history
(FHH) and genomics in a Singaporean population. Secondly this study will evaluate the
facilitators and barriers to implementation of a family history collection and risk
assessment tool within a Singaporean population.
Description:
This study is a collaboration between Duke University School of Medicine Center for Applied
Genomics and Precision Medicine (CAGPM) and the National Heart Center of Singapore (NHCS) and
SingHealth Duke-NUS Center for Precision Medicine (PRISM). The NHCS study, Molecular and
Imaging Studies of Cardiovascular Health and Disease ("Biobank study") is collecting genomic,
clinical, and environmental data on a large cohort of healthy Singaporean volunteers. Data
from the Biobank study is being deposited into a large healthy population cohort database,
SPECTRA, organized under PRISM. The investigators will collaborate with the NHCS Biobank
study and PRISM to integrate the Duke family history risk assessment platform, MeTree, into
the data collection of the Biobank study cohort for in-depth analyses of FHH and genomic
associations as well as exploration of the feasibility of MeTree implementation into the
Singaporean clinical context. The Biobank study is a prospective observational study. It has
already enrolled 1,000 subjects and will continue enrollment over the next year and possibly
beyond. Previously enrolled subjects will be re-contacted for completion of MeTree as well as
having future enrollees complete the tool prospectively. The investigators anticipate 5,000
subjects completing MeTree over a one-year period. The investigators will evaluate the
feasibility and effectiveness of implementing MeTree in the larger Singaporean context. The
investigators will assess implementation related outcomes- questions/problems people have
when completing their family histories, how complete are the FHH entered, what types of risk
are identified and what existing programs in Singapore are designed to manage that risk. The
completion of this project will provide a significant amount of data to better understand the
associations between FHH and genomic data within a healthy Asian population. It also will
result in a better understanding of an appropriate implementation strategy for MeTree within
the Singaporean clinical setting.
Specific Aim 1: To explore the correlation of genomic data and FHH within a healthy Asian
population.
Specific Aim 2: To assess the clinical utility and appropriateness of a patient-entered FHH
risk assessment tool within a Singaporean population.
Specific Aim 3: To create an implementation strategy for broader implementation of a
patient-driven risk assessment tool in Singapore.
Duke University will be providing access to the MeTree Family Health History tool, storage of
the PRISM participant data, participant and provider risk assessment reports, and education
about the tool to PRISM study staff as needed. Duke University personnel will not be involved
in any recruiting, consenting, or follow-up with study participants, but will have access to
de-identified participant data housed in the MeTree research database in order to provide
support for the study coordinators for participant account trouble-shooting and also to
provide interim and final datasets to the PRISM statisticians. The MeTree research database
currently sits on a DHTS server behind the Duke firewall, and is maintained and secure in
accordance with Duke policy for patient data.
