Genetic Analysis of Inherited Urologic Malignant Disorders: Collection of Samples
NCT00001814
Adenoma, Adenoma, Oxyphilic
Bethesda, Maryland, United States
View Trial DetailsNCT Number: NCT05079334
Investigators from Vanderbilt University Medical Center (VUMC), Duke University, and Meharry Medical College (MMC) are collaborating on a family health history study to deploy a family health history (FHH) platform, MeTree. Recruited participants will complete surveys, the MeTree questionnaire, and MeTree will determine the participant's cancer risk based on current guidelines. The study team will offer genetic counseling to high-risk participants. Investigators will track participant outcomes and behaviors from the use of MeTree to determine the efficiency of the use of MeTree compared to completion of pedigrees in clinic.
Looking for future studies?
Notify Me18 year and older
All sexes
Observational
Meharry Medical College, Nashville, Tennessee, United States
From the earliest recognition of cancer-prone families over 100 years ago, clinicians have depended on the family health history (FHH) to identify and treat patients and family members who may have a cancer family syndrome. Once identified, patients can be offered lifesaving, evidence-based management strategies for many of these conditions. To fully realize the benefits of genetic healthcare, however, at risk individuals must be recognized, offered genetic counseling and testing, and then referred for specialized therapy or enhanced screening. While this is a promising time for these patients and families, there are significant challenges to implement a modern and efficient care delivery model across the many patients, provider, and health system stakeholders.
The practice of genetic medicine is changing as genetic discoveries are translated into new tests for an increasing number of health indications. In fact, the prevalence of high-risk individuals who are at risk for hereditary cancer has been rising due to new testing strategies. This has placed enormous pressure on the hospitals and clinics providing care for high-risk patients. Coupled with the healthcare systems need for greater efficiency, the traditional genetic clinic-based practice has become untenable. Barriers and challenges include low numbers of trained genetic workforce, lack of integrated FHH tools for patients and physicians, and long wait times for available clinic appointments. Further, while cancer syndromes are seen across all groups, gaps in care exist as underserved populations are often not recognized and referred for care.
Investigators propose that these barriers can be overcome by using innovations in informatics and telecommunications to develop a sustainable and scalable genomic care delivery model that can be replicated by other health systems. Such a program would need to integrate FHH applications that collect and analyze family data, SMART-on-FHIR capabilities that can link third party apps with the electronic medical record (EMR), and clinical decision support modules to assist providers and patients. MeTree is one such system with all these capabilities -- a validated and flexible patient-facing FHH collection tool that supports SMART-on-FHIR technology. This platform was the backbone of the Implementing Genomics in Practice (IGNITE) network's FHH clinical utility study that showed clear improvements in the quality and quantity of FHH collected in 5 geographically diverse primary care practices. Furthermore, MeTree was highly acceptable to patients and providers, and was able to properly identify participants at risk for 23 hereditary cancer syndromes for genetic counseling referral.
Our re-submission for this Beau Biden Moonshot grant opportunity is based on the hypothesis that an implementation science approach will improve the identification and management of high-risk patients from diverse clinical setting by systematically integrating FHH driven evidence-based guidelines into the EMR. Investigators plan to improve ascertainment of high-risk patients by imbedding MeTree in the workflow of primary and cancer care clinics. This will improve identification for genetic counseling, facilitate patient education about genetic testing, and risk management for at risk patients, as well as facilitate engagement of patients, family members, and providers with telegenetic and telephone counseling options. This collaborative effort from genetic, genomic, biomedical informatic, and implementation science researchers at Vanderbilt University Medical Center (VUMC), Meharry Medical Center (MMC) and Duke University is highly responsive to the five required elements in RFA-CA-19-017. The proposal has the following specific aims:
SA1. Deploy a care delivery model that will facilitate systematic risk assessment for hereditary cancers in diverse clinical environments.
SA2. Improve access to genetic healthcare providers for participants at risk for hereditary cancer syndromes.
SA3. Explore the feasibility of our care delivery model to improve family engagement for cancer risk assessment
Healthy volunteers accepted: Yes
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
Time frame: From enrollment to study completion (up to 3 years)
Proportion of participants sent a MeTree link who complete the MeTree family health history questionnaire, defined by generation of a MeTree risk report. Engagement steps (link clicked, account created) will be summarized descriptively. 95% confidence intervals will be reported using the Wilson method; subgroup comparisons by site and demographics will be exploratory.
Time frame: Assessed at two time points: baseline (pre-MeTree, using all available prior EHR history) and 12 months after MeTree completion.
Billing code based identification of personal or family history indicators of hereditary cancer
Time frame: At the genetic counseling appointment (index visit) occurring after MeTree results review and within 12 months after enrollment.
Length of genetic counseling appointments in minutes
Vanderbilt University Medical Center
Other
Improving Identification and Healthcare for Patients With Inherited Cancer Syndromes: Evidence-based EMR Implementation Using a Web-based Computer Platform
Acronym: FOREST
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
Published trials that share one or more normalized conditions with this study.
NCT00001814
Adenoma, Adenoma, Oxyphilic
Bethesda, Maryland, United States
View Trial DetailsNCT00001377
Congenital, Hereditary, and Neonatal Diseases and Abnormalities, Genetic Diseases, Inborn
Bethesda, Maryland, United States
View Trial DetailsNCT07053813
Congenital, Hereditary, and Neonatal Diseases and Abnormalities, Genetic Diseases, Inborn
Denver, Colorado, United States
View Trial DetailsNCT04903782
Cancer, Congenital, Hereditary, and Neonatal Diseases and Abnormalities
Newcastle, New South Wales, Australia
View Trial Details