Improving Identification and Healthcare for Patients With Inherited Cancer Syndromes: Evidence-based EMR Implementation Using a Web-based Computer Platform
Conditions: Neoplastic Syndromes, Hereditary, Comparative Effectiveness Research
Sponsor: Vanderbilt University Medical Center

Family History and Cancer Risk Study 
NCT NCT05079334 
IRB 201202
Protocol
7/9/24

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FOREST (Family History and Cancer Risk Study) 
 
Georgia L. Wiesner, MD 
Director, Vanderbilt Hereditary Cancer Program Ingram  
Professor of Cancer Research and Medicine  
 
Created: November 27, 2019 
Revised: April 6, 2020, June 29, 2021, September 17, 2021,  
October 26, 2021, July 14, 2022, January 30, 2023, June 5, 2023, July 9, 2024 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Table of Contents: 
 
 
Study Schema 
1. 
Background 
2. 
Rationale and Specific Aims 
3. 
Inclusion/Exclusion Criteria 
4. 
Enrollment/Randomization 
5. 
Study Procedures 
6. 
Reporting of Adverse Events  
7. 
Study Withdrawal/Discontinuation 
8. 
Statistical Considerations 
9. 
Privacy/Confidentiality Issues 
10. 
Follow-up and Record Retention 
11. 
Substudy (VUMC-specific) 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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1. 
Background 
 
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 familial cancer 
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 patient, 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 system’s 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 platforms 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. 
MeTree is a computer platform that has been developed by researchers at Duke University that electronically 
collects FHH information for hereditary cancer syndromes and other health conditions directly from the patient. 
MeTree then calculates hereditary cancer risks for the patient and creates a personalized patient report and 
evidence-based clinical decision support for the provider. In previous studies, MeTree demonstrated 
improvements in the identification of those at risk and highlighted ongoing challenges particularly around 
undergoing genetic counseling and testing, and awareness of risk.  Co-investigators from Duke/MeTree 
collaborate on this grant. 
 
2. 
Rationale and Specific Aims 
 
SA1. Deploy a care delivery model that will facilitate systematic risk assessment for hereditary cancers 
in diverse clinical environments. 
● Up to 3,500 participants will be enrolled and complete the MeTree FHH risk assessment 
● Deploy in 2 academic medical centers; Vanderbilt University Medical Center (VUMC) and Meharry 
Medical College (MMC)  
● Assess participants perceptions using online survey and qualitative semi-structured interviews 
SA2. Improve access to genetic healthcare providers for participants at risk for hereditary cancer 
syndromes.  
● 300 high risk participants in the VUMC Hereditary Cancer Clinic will be enrolled  
● Extend clinic capacity by lessening the need for in-clinic family history collection and basic counseling  
● Expand reach of clinic by using telephone and video genetic counseling; referral to specialists 
SA3. Explore the feasibility of our care delivery model to improve family engagement for cancer risk 
assessment  
● Participants extend invitations to family members to MeTree’s family resource center to share results of 
genetic tests  
● Assist with education and referral needed for cascade testing for pathogenic variants 
 
 
 
 
 
 

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3. 
Inclusion/Exclusion Criteria 
 
Inclusion 
● Receiving medical care at Vanderbilt University Medical Center or Meharry Medical College 
● Age 18 years or older 
● Able to read and communicate in English 
● Willing to use the Internet 
● Current My Health at Vanderbilt (MHAV) user or willing to sign up and use (Vanderbilt participant 
requirement only) 
 
Exclusion 
● Non-VUMC/MMC patients 
● Diagnosed with a terminal illness 
● Unable to speak/read English 
● Unable/unwilling to use the Internet (specifically MeTree) 
● Previous genetic testing and/or counseling through the Hereditary Cancer Clinic 
4. 
Enrollment 
 
Participants will enroll through My Health at Vanderbilt (MHAV)*.  MHAV is VUMC’s patient portal where the 
patient may sign up and participate in managing his/her health care.  MHAV can also be used for sending 
mass research recruitment messages to a predefined cohort of patients who meet certain study-specific 
inclusion/exclusion criteria, have explicitly said OK to Contact for research purposes, and have an active 
MHAV account. The messaging process is managed centrally by the VICTR/Health IT teams, sending the 
messages on behalf of the study team.     
 
     MHAV:      Initial e-mail notification the patient receives about the research study invitation 
 
1. If patients have email notifications turned on, they will receive the standard, system-generated 
email stating they have a research invitation.  
“You have a new message in My Health at Vanderbilt! Please sign in to read your 
message. 
Thanks for using My Health at Vanderbilt, 
Vanderbilt University Medical Center” 
2. Once a patient logs in, they will be taken to the research studies dashboard and will see the 
following patient-friendly study title and description under the heading “Studies you may be 
able to join”. 
  
                    Once a patient clicks on the link from the email/text notification or from the MHAV homepage, 
he/she will be taken to the Research Studies page.  Here the new study will be listed under the heading – 
Studies you may be able to join – with the following information (Appendix H): 
 
 
If a patient clicks, I’m Interested, the REDCap Participant Updater Module will create a record in the study 
database that includes patient MRN and the enrollment status of Interested. Once the Updater Module creates 
a new record, it will trigger REDCap to fetch the email address to facilitate sending the follow-up email from 
REDCap, which will include more information about the study and a link to the survey.    

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If a patient clicks, No, Thank You, the REDCap Participant Updater Module will create a record in the study 
database that includes patient MRN and the enrollment status of Not Interested.  This will prevent any further 
communication to the patient about this study. 
 
Once the eligible participant enters the REDCap study pre-screen, they will be able to complete the eligibility 
survey, electronic consent, and pre-MeTree survey.  At the end of the pre-MeTree survey, participants will be 
given a link to the MeTree platform to begin the questionnaire.  At any time, they can leave MeTree and re-
enter by using the link from the REDCap message or by the link in their MHAV portal.  Participants will receive 
a $10 gift card for completing the eligibility, eConsent, and pre-MeTree surveys. 
 
After completing the eligibility, eConsent, and pre-MeTree surveys, participants will receive an email with the 
link to MeTree (Appendix K). Participants have three weeks to complete their MeTree questionnaire.  After 
completing the questionnaire, participants will receive a report from MeTree. After receiving the report from 
MeTree, and once the study team has concluded the enrollment of the 3,500 participants, 300 “high risk” 
participants will be referred to the Hereditary Cancer Clinic to discuss their results with a Genetic Counselor.  
The consent will include information about this step to inform participants that they may be contacted for 
counseling. 
 
*My Health at Vanderbilt (MHAV) language is used to describe the workflow at Vanderbilt. 
 
 
5. 
Study Procedures 
 
 
As described in Section 4, participants will be recruited and enrolled electronically. * This process will take 
approximately 30-45 minutes, depending on the answers to screening questions.  Once enrolled, they will be 
asked to complete the MeTree Family Health History (FHH) questionnaire (See Appendix A for actionable 
conditions, Appendix B for actionable recommendations, Appendix C for MeTree participant report example, 
and Appendix D for MeTree provider report example). 
 
Upon entry into the MeTree platform, participants will be able to immediately enter FHH information into the 
program or download the worksheet for collecting the information requested by MeTree from family members 
and return later to enter the information into the MeTree platform (The printable worksheet is named Appendix 
E).  The time involved to complete MeTree may vary significantly depending upon the number of relative’s 
participants enter data on and the availability of the FHH information.  This will be mitigated by providing a 
smart link to finish the FHH in pieces, rather than all at once. Participants are advised in the consent form that 
answering the FHH questions may make them uncomfortable.   
 
For participants who may want additional instructions for the MeTree questionnaire, we will provide a how-to 
power point (included as Appendix F).  
 
Vanderbilt: Participants who do not access MeTree within 30 days of consent will be sent reminder emails 
once per week for up to 4 weeks.  Once participants complete data entry in MeTree and the post-MeTree 
survey, participants will be sent a $20 gift card. Participants will be sent a web-based survey via an email link 4 
to 6 weeks after completing MeTree (post-MeTree survey). If the survey is not completed within 1 week of the 
initial invitation, reminder emails will be sent weekly for up to 4 weeks. Participants will receive a $20 gift card 
for completing the post-MeTree survey. 
 
 
 

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Meharry: For enrolling and completing the baseline (pre-MeTree) survey, participants will receive $10 cash (if 
on site) or Amazon or Visa gift card (sent to your home). For the completion of the MeTree questionnaire, 
participants will receive an additional $50 cash (if on site) or gift card. Participants may receive $10 cash or gift 
card for any additional surveys after completing the MeTree questionnaire. 
 
Once data entry in MeTree is complete all participants will receive a personalized patient report within the 
platform outlining their familial and genetic risk status the included medical conditions according to current 
evidence-based guidelines. Participants’ providers will be notified via one of several methods (email without 
PHI, EPIC messaging, or an alert) that their patient has a MeTree clinical decision support report available in 
the medical chart (accessible via a SMART link).  Outside providers will receive an email or letter.  The 
templates for these messages is located in Appendix I. The process to upload the MeTree report and provide 
accessibility to providers is approved by the Medical Forms Committee and the Center for Health Information 
Management (CHIM) Committee.   
 
As previously stated, in Aim 2 participants who are identified as at high genetic risk (n=300) will be contacted 
by the study nurse (as part of their standard of care) to schedule a genetic counseling appointment (Appendix 
J, High risk patient email). The number and length of genetic counseling appointments will be recorded in order 
to evaluate the change in clinic capacity for those with a pre-recorded FHH in the MeTree platform as 
compared to routine patients who have not participated in the study and completed MeTree. The frequency of 
genetic testing and outcomes of the testing will also be recorded in REDCap from data collection in the 
Hereditary Cancer Clinic at VUMC. 
 
To analyze the time saved by completing MeTree prior to a clinic visit, the study team will perform a 
retrospective review of control patients, selected by the study team, to assess the amount of time in clinic with 
the genetic counselors.  This will be done through time stamps in eStar and chart review.  Control patients will 
not be a part of the study, nor will their information be shared with anyone.  The study team will only review for 
time spent in clinic versus the study participants’ clinic visits. 
 
Additionally, genetic counselors who see participants from this study will be surveyed to better understand their 
perspective of the use of MeTree.  This portion of the study will be in a separate IRB. 
 
To promote awareness of the need for cascade testing among relatives, participants who undergo genetic 
counseling and testing in the Hereditary Cancer Clinic and are found to have a strong family history and/or a 
pathogenic gene mutation, will be encouraged to share the study information with family members (Aim 3). We 
will not ask for identifying information regarding their family members.  The study team will only accrue data on 
how many times the participant’s MeTree web link was shared and accessed (clicked on).  Patients are not 
required to share any information with family members if they feel uncomfortable. 
 
The timeline below reflects an individual’s timeline from entry into the study.   
 

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*We will attempt to enroll participants electronically when possible.  However, we understand that there are 
some participants who may not be able to enroll electronically and manual enrollment (by paper, tablet, or 
phone) will be available and will conform to all CDC pandemic guidelines. 
 
As a result of reviews from the first third of completed MeTree reports, a notes section was added to the 
MeTree reports to indicate any versioning/changes to the report.  The notes will include any changes to the 
report (such as an updated pedigree) and where they can be found.  If any technical or clinical changes are 
made to reporting, participants may receive an updated report, and will be notified if an updated report is 
available.  Updated reports may or may not affect their high-risk report status or report recommendations.  
 
 
6. 
Reporting of Adverse Events or Unanticipated Problems involving Risk to Participants or Others 
 
All researchers will report all events that are serious, unexpected, and study-related to the PI by phone, fax or 
email within 24 hours of becoming aware of the event. We will promptly report to the IRB any participant 
complaints about the conduct of any element of the study or concerns about potential harms, including copies 
of any written communication with the participant addressing those concerns. Further, all conversations with 
participants that indicate a level of concern about a study component - even if not a complaint - will be 
documented and distribution of any participant education materials in response to such queries will be 
documented in the participant’s research (REDCap) record. 
 
 
7. 
Study Withdrawal/Discontinuation 
 

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Participants can choose to stop being a part of the study at any time.  Vanderbilt participants will need to 
notify the study team either by a phone call to (615) 936-2660 or email to FOREST_Team@vumc.org.  
Meharry participants will need to contact the study manager, Dr. Clasherrol Edwards, at (615) 327-5519 or 
forestteam@mmc.edu. 
 
  The participant may be taken out of the study if:  
 
● 
They do not complete the MeTree Survey within 12 months of enrolling 
● 
If they move out of the state 
● 
Or stop receiving care at VUMC or Meharry Medical College 
 
 
Withdrawing participation 
We will continue to utilize the participant data in analyses unless the participant asks for the data to be 
withdrawn. Data will still be within the EHR, MeTree, and the research database (REDCap), but data will be 
excluded from analyses.  
 
Active declining participation 
Some participants may begin the study but at some point, feel uncomfortable continuing to participate.  
Participants who decline to further participate may withdraw from the study if they wish.  If the participant 
declines to continue and alerts the study team, the protocol above will be followed.  If the participant declines 
to proceed any further, study data will continue to be used in pertinent analyses. 
 
Surveys of declination or withdrawal 
Participants that decline or withdraw from the study will be asked why they are making this choice.   
 
Non-responders (Passive Decline)  
Participants who enroll but do not complete the MeTree questionnaire or subsequent surveys will be treated as 
enrolled but excluded participants (i.e., non-responders).  Participants who are delayed in filling out the 
questionnaire but still complete the questionnaire prior to analyses of the data will be included, despite the 
delay.  
 
Deceased participants 
The study will utilize the data of deceased participants even if they pass before the conclusion of the study. 
 
8. 
Statistical Considerations 
 
We will use a case-control design for statistically analyses. Cases are defined as the study participants who 
have completed the MeTree tool (intervention). We will utilize data from the Hereditary Cancer Clinic registry 
(IRB # 141203) to fine patients identified at risk of a hereditary cancer syndrome in the usual care (control) and 
intervention conditions. The control condition utilizes historical data from the participants prior to their 
enrollment date in FOREST to determine the number and proportion of participants who would be identifiable 
as at risk without the implementation of MeTree.  We believe this is the most effective method to analyze the 
MeTree platform’s effect on hereditary cancer testing and outcomes.  Power calculations estimate a sample 
size of up to 3,500 (minimum of 3,000) is needed to produce statistically significant results.  
 
In the graph below, the blue line represents 90% power to detect the primary endpoint with a p-value of 0.05, 
the green line, 85% power, and the red, 80% power. The x-axis represents how many participants are 
identified as being at high risk by MeTree. 
 

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In prior studies of primary care populations, on average 20% were newly found to be at high risk (had not 
previously identified). However, in order to accommodate differences in a population that has a proactive 
hereditary cancer clinic, we used a lower estimate of 10% for the power analyses. Thus at 10% risk 
identification and 95% power we estimated that we would need at a minimum 1,000 participants for a single 
site and 2,000 participants total to detect differences in identification at the 2 sites (Meharry and Vanderbilt). In 
addition, these participants flow into aim 2. Based on power analysis to detect an increase in clinic capacity, 
we need to have 150 high risk patients who complete MeTree in Aim 1 to see a genetic counselor in the 
hereditary cancer clinic at Vanderbilt. At a 10% identification rate and a 50% follow up rate (estimate based on 
literature review and the clinic’s attendance rate), a minimum of 3,000 participants will need to complete 
MeTree in Aim 1. We are therefore enrolling 3,000-3,500 participants for this study.  
 
Data elements considered for this analysis: 
Primary Endpoint: Participant designated as high risk for cancer. 
Assessment pre: chart review (any indicator prior to MeTree, not time-frame dependent)  
Assessment post: MeTree report (measured when the report is generated, independent of amount of follow-up 
time) 
Hypothesis: MeTree will increase the proportion of high-risk individuals identified. 
Statistical interpretation of the hypothesis: P(of high risk) is a function of the intervention 
 
 
9. 
Privacy/Confidentiality Issues 
 
The study data live in a REDCap database.  This project will utilize the REDCap platform for data collection 
and management.  Project team members listed as Key Study Personnel with existing electronic health record 
(EHR) system access rights may also be granted use of REDCap Clinical Data Interoperability Services (CDIS) 
tools.  These tools are designed to enable transfer of relevant study-related data from the Vanderbilt Research 
Derivative and/or directly from the EHR into REDCap. 
 
Participant answers to the survey are linked only to a study ID number in a password protected electronic 
database. Only study staff will have access to the information, and any paper records are kept in a locked drawer 
in the study manager’s desk. Pragmatic studies are considered minimal risk. All data will be gathered and stored 
using protocols and privacy & security standards that comply with HIPAA and, where applicable, GINA. All patient 
FHH data will be gathered from patient portal applications and transmitted to and from the algorithm and clinical 
decision support databases using industry standard encryption protocols, including HTTPS and TLS. The 
healthcare systems employ additional protections for the data, including detailed audit logs, insulation from direct 
SQL queries, and detailed version control. 
 

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While participant data such as demographics are collected from the VUMC Epic instance, data are delivered by 
SFTP to the MeTree platform, housed at Duke University, for participants to complete the FHH questionnaire.   
FHH results will be transmitted by API to a secure REDCap project at VUMC or MMC. * 
 
*This process is approved by the VUMC Architecture Review Board. 
 
All data gathered for the proposed studies will be treated with the same degree of confidentiality as a medical 
record. Confidentiality will be maintained for the identity of participants in this study except as necessary for 
oversight by the Secretary of the Department of Health and Human Services or his designated representative. 
Only group information without personal identifiers will be included when sharing process implementation data 
and outcomes with approved collaborators. FHH data collection is already considered standard of care for 
medical practice and the risk associated with this information or risk-based prevention strategies is considered 
to be no more than that associated with routine clinical care.  
 
At the beginning of the study, participants will provide the study team with their VUMC health care provider’s 
name.  After the participant completes the MeTree questionnaire, a message will be sent to the provider via 
REDCap to their eStar message basket alerting them that their patient has completed the questionnaire and 
that there is a provider-version report available for them to view.  The provider can click a link in the message 
and be sent to MeTree, where they can locate the report.    
 
For contact purposes, we will give participants the option to provide a secondary contact in case the participant 
cannot be reached.  This will only be used if the study team loses contact with the participant (i.e., phone line 
disconnected, email no longer active). 
 
Regardless of primary or secondary findings, the participant is allowed to provide any findings to their family.  
The study team will not contact family members of the participants, even in the case of death. 
 
 
10. 
Follow-up and Record Retention 
 
The study will last 4 years.  Paper records will be kept for up to six years after the study ends. Electronic data 
will be kept indefinitely.  Research data entered into REDCap will be kept for an unknown length of time. 
 
 
11. 
Subproject of Family History and Cancer Risk Study (FOREST): Building 
more inclusive sex- and gender-related questions for genetics research 
 

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Table of Contents 
1. Background 
2. Rationale & Specific Aims 
3. Inclusion/Exclusion Criteria 
4. Enrollment 
5. Study Procedures 
6. Reporting of Adverse Events  
7. Study Withdrawal/Discontinuation 
8. Analytic Considerations 
9. Privacy/Confidentiality Issues 

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1. Background 
It has been less than a decade since the legalization of same-sex marriage; a fact that seems to be 
forgotten by many.  While society has made great strides in the inclusion and acceptance of the 
LGBTQIA+ (lesbian, gay, bisexual, transgender, queer, intersex, asexual, and other marginalized 
sexual orientations and gender identities) community, there is still much to be done. As of June 2, 
2023, there are 491 anti-LGBTQ+ bills up for vote in the United States. Our healthcare system and 
research institutions are failing transgender, non-binary, and intersex individuals, as demonstrated by 
numerous health disparities among these populations and barriers to healthcare. Research has 
shown the importance of collecting gender identity data as well as surgical history and organ/tissue 
inventory to ensure equitable healthcare for transgender and non-binary individuals. However, some 
research studies do not include gender identity questions. Furthermore, when these questions are 
included, this data may not be used in ways that benefit transgender, intersex, and non-binary 
participants. When gender identity data is collected, it is not usually performed in a standardized 
manner, and most existing sex- and gender-related measures (SGM) were not developed in 
collaboration with members of the transgender, non-binary, and intersex communities. Research 
shows that members of this community often feel uncertain of how to answer SGM or find existing 
SGM to exclude or marginalize them further. These impacts may contribute to this community’s 
distrust towards research and fear of discrimination in healthcare. 
 
Automated processes are increasingly utilized throughout the healthcare field and research. These 
automated processes often rely on the electronic health/medical record (EHR/EMR) and/or 
demographic information obtained from patients. Due to the increased use of automated processes, it 
is critical that gender identity information is not only documented, but documented accurately to avoid 
harm to individuals, such as misgendering participants. The failure to identify transgender patients 
can lead to improper care of patients. Many patients alter their originally recorded legal sex to match 
their gender identity. For example, if someone changed their sex on their identifying documents from 
female to male they may be identified within the EMR system as male. Even for patients who do not 
change their legal documentation, organs and tissues change when participants undergo transition-
related medical care, so these patients may have tissues that are not associated with their 
documentation (e.g., transgender women with breast tissue who still have a legal sex of male). 
Automated processes that drive reminders for important screening methods for ovaries, uterus, 
breast tissue, cervix, and other organs and tissues could be missed, thus increasing this individual’s 
risk of illness or disease. 
 
The Family History and Cancer Risk Study (FOREST) is evaluating an automated hereditary cancer 
risk assessment (MeTree) with referral to genetic counseling for those deemed to be “high risk” for a 
hereditary cancer syndrome. Evaluations of the responses from already enrolled transgender and 
non-binary participants within the FOREST study show that the SGM utilized were interpreted 
differently by participants. For example, the FOREST question about sex was sometimes interpreted 
to be asking about a person’s sex assigned at birth, while other times it was interpreted as 
representing gender identity. Because the MeTree risk calculations rely on sex-related information 
provided by participants, it is of clinical importance to have valid measures for these variables. These 
differences in interpretation of the same question demonstrate a critical need for redesign and 
standardization of SGM for research studies and clinical care, especially as relates to genetics care, 
which requires knowledge of both sex assigned at birth (for risk algorithms), and detailed information 
about phenotypic sex, hormonal milieu (mixture of endogenous and exogenous hormones), and past 
procedures (e.g., organ removal) to inform appropriate genetic risk management. For example, a 

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person who is receiving gender-affirming surgeries or hormone care may need screenings not often 
provided for those of their assigned sex at birth (ASAB; e.g., mammograms are not typically provided 
for people assigned male at birth, but may need to be provided for transgender women and other 
people assigned male at birth who develop breast tissue from exogenous gender-affirming hormone 
therapy). Similarly, knowledge of hereditary cancer risk can inform choice of surgical procedure for 
chest reconstruction for patients seeking breast tissue removal and inform needed screenings for 
patients who have already had this procedure. As a result, routine family history risk assessment is a 
critical component of transgender care – but unfortunately, this component is often overlooked. 
 
2. Rationale & Specific Aims 
To reduce potential harms, thoughtful and inclusive standardized SGM and guidelines for ethical data 
collection and usage need to be developed in collaboration with members of the transgender, gender- 
and sex- diverse (TGSD) communities. We have chosen the terminology TGSD to broadly 
encompass a subset of individuals from the NIH Sexual and Gender Minorities definition, those 1) 
who are transgender, non-binary, or intersex, 2) whose gender identity does not align with their sex 
assigned at birth, 3) who have a difference of sex development, or 4) whose gender identity or 
expression, or reproductive development is characterized by non-binary constructs of gender and/or 
sex. To this end, we plan to conduct semi-structured interviews with TGSD individuals who 
participated in the FOREST study to understand their interpretations of the SGM used. Additionally, 
we aim to evaluate the potential clinical and psychosocial harms associated with use of various SGM 
data models used in genetics, including that used in FOREST. We will obtain participant’s advice for 
improving upon the MeTree SGM and guidance on usage of this data in automated systems. This 
information will be used to provide recommendations for the thoughtful and inclusive standardization 
of those questions for future genetics studies and in genetics clinical care. We hypothesize that in 
semi-structured interviews participants will elucidate gaps in the MeTree and FOREST SGM, reveal 
potential social and clinical harms associated with current models, and provide recommendations for 
designing thoughtful and inclusive SGM. These recommendations for SGM will provide greater 
validity for incorporation into automated care processes. In semi-structured interviews we will: 
 
Aim 1. Explore TGSD participants’ interpretation of SGM used in the FOREST study to assess 
measure validity.  
We will evaluate TGSD participants’ interpretation of SGM used in the FOREST study, as well 
as alternative question/response formats from the literature. These descriptive evaluations will 
provide insight into the validity of sex- and gender-related question/response structure used in 
FOREST as well as alternative formats. 
 
Aim 2. Evaluate the psychosocial and clinical impact of SGM on TGSD participants and assess 
harms.  
We will evaluate potential individual- and group-level psychosocial and clinical harms of the 
FOREST study design. The results of this aim will inform a framework for ethical collection and 
usage of sex- and gender-related data.  
 
Aim 3. Ascertain participant recommendations for ethical collection and use of SGM in clinical 
genetics and translational genetics research, especially those reliant on automated 
processes.  
We will provide participants with study reasons for collecting sex- and gender-related variables 
in genetics care and collect participant recommendations to improve the performance of SGM 

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in this population, with particular attention to questions and/or answer choices that participants 
found confusing or harmful. Further, we will ascertain participant-guided recommendations for 
automated processes that rely on sex- and gender-related variables.  
 
The data from Aims 1, 2, and 3 will inform a final ethical framework for sex- and gender-related data 
collection and usage in genetics studies, including incorporation into automated processes. Together 
these aims will allow us to propose updated measures for sex- and gender-related variables for 
MeTree that are directly guided by members of the marginalized community these questions intend to 
benefit.  We expect that these standardized questions and responses, developed in collaboration with 
TGSD individuals with genetics applications in mind, will reduce clinical and psychosocial harms to 
future participants and patients in both genetics research and clinical genetics settings by improving 
the accuracy of data collected and participant/patient experiences. Additionally, we anticipate that 
involving the community in the co-creation of standardized SGM and recommendations for their 
usage will improve these populations’ trust of research and the medical system. 
 
3. Inclusion/Exclusion Criteria 
 
3.1. Inclusion:  
 
● Participants will have been previously consented to and enrolled in The Family History and 
Cancer Risk Study (FOREST).  
○ As a result, participants will meet FOREST eligibility criteria: they will be 18 years of age 
or older, English-speaking, and, if a Vanderbilt patient, have a My Health at Vanderbilt 
(MHAV) account.  
● Identified via the EHR (using diagnosis, procedure, or billing codes or gender identity/sex 
assigned at birth data) to be TGSD, or identified via responses on the FOREST survey or the 
MeTree family history application with a response consistent with being TGSD, or responses 
on MeTree that they prefer not to disclose a gender identity or do not know their sex assigned 
at birth (“Unknown”). Note that FOREST consented participants have already consented to the 
use of FOREST-collected data and their EHR data by the main study. 
○ The following response selections on FOREST and MeTree will be considered eligibility 
criteria for recruitment to interview: “Other” for the FOREST survey question of “Sex”; 
“Other” or “Unknown” for the MeTree question of “Birth sex”; “Non-binary,” “Transgender 
male-to-female,” “Transgender female-to-male,” “Other,” “Unknown” or “Prefer not to 
respond” for the MeTree question of gender identity. Further, we will also include 
FOREST participants who have any discordant responses amongst these three 
questions (e.g., those who respond “female” to birth sex and “male” to gender identity), 
or have an inconsistency between their legal sex in the EHR and their sex assigned at 
birth in the EHR or their reported FOREST data. We will also include FOREST 
participants who have EHR diagnosis codes consistent with TGSD identities or 
receiving gender-affirming care.  
○ Because not all FOREST participants have completed MeTree, we will also use a 
predefined set of EHR-coded data to identify other TGSD participants among enrolled 

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FOREST participants. These codes have been previously validated in another study 
(Bick et al., in preparation). 
● Must consent to participate in a recorded and transcribed qualitative interview for formal study 
analysis 
 
3.2. Exclusion:  
 
● Not a FOREST participant 
● Does not meet substudy definition of TGSD described above 
● Does not consent to recorded interview 
 
4. Enrollment 
 
Recruitment will begin after the substudy has been approved by the IRB and will occur on a rolling 
basis as individuals who meet eligibility criteria are added to the main FOREST study. Invitations will 
be sent via email to FOREST participants who meet the substudy eligibility criteria defined above. 
Follow-up phone call(s) will occur to email non-respondents to enroll participants. Attempts will be 
made to reach participants up to four times by phone/email. Participants who respond favorably to 
email or phone within that time will have follow-up communication regarding scheduling for a follow-
up semi-structured interview. To ensure that we have a large enough pool of eligible FOREST 
participants who meet eligibility criteria for this substudy, we will also enhance FOREST recruitment 
efforts in clinic and community areas that reach VUMC TGSD patients. For this we will distribute 
FOREST recruitment materials in the adult transgender clinic at VUMC and to LGBTQ+ community 
interest groups (both online and in person) in the greater Nashville area. In both recruitment avenues, 
we will tailor recruitment materials (see documentation included in the amendment) to inform TGSD 
adults of the relevance of hereditary cancer risk assessment to their health care and to acknowledge 
that we are interested in enrolling TGSD participants for additional interviews about how to make the 
study more inclusive. These additional materials, as well as all materials associated with this 
substudy, were designed with the oversight of Mx. Bland and Dr. Mittendorf, two transgender 
members of the FOREST research team. 
 
Participants who agree to be interviewed in the substudy will either be allowed to use the web 
conference link to secure software or will be phoned out from secure software, based on participant 
preference at the time of their scheduled interview. We will use a secure Microsoft Teams web 
conference or Microsoft Teams web conference phone call; Microsoft Teams is VUMC-approved 
secure software for this purpose. Prior to the interview, we will send the participant the eConsent link.  
They can choose to read and sign before the interview or go through the consent with the interviewer 
on the phone. Before the interview begins, the interviewer will confirm that the consent is signed and 
if the participant has any questions. 
 
  
 
 
5. Study Procedures 
 

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As described above, participants will be recruited through a mixture of electronic and telephone 
recruitment procedures. Eligible FOREST participants will be contacted up to four times via email 
and/or phone with the purpose of offering participation in the substudy. In order to track the number of 
contacts and content of contact, we will record this information in the main FOREST study REDCap 
used for participant contact tracking. Additional contacts may occur to facilitate interview scheduling 
or field questions of potential interviewees. A potential participant may request that we cease 
contacting them about an interview at any time. Participants who state they are not interested will not 
be further contacted and their desire for no further contact recorded in the study tracking system. 
Further, participants who are unable to be reached after four contact attempts will be considered non-
responders to substudy outreach, and recruitment attempts for the interview substudy will cease. The 
email sent and recruitment phone voicemail intentionally contain no mention of the relevance of the 
interview to TGSD participants explicitly, in order to avoid accidentally outing TGSD participants to 
unsupportive family or associates. Instead, participants who answer the phone and speak to the 
recruiter or who respond favorably to an email request for interview will be provided details about the 
subject of the interview at that time. Participants who agree to participate will be scheduled by phone 
or email for an interview with a study staff member trained in qualitative interview methodology.  
 
Participants who agree to be interviewed in the substudy will be phoned at the time of their scheduled 
interview from a secure Microsoft Teams conference line, which is VUMC-approved secure software. 
They will be read a structured consent document and asked for verbal consent. We will request to 
begin recording prior to consent being read. The consent will then be recorded via Microsoft Teams. 
During the consent process, participants will be informed that they can choose to skip any question or 
end the interview at any time due to psychological discomfort. We will reconfirm participant consent to 
continue recording the interview at the end of the consent process.  Consented interviewees will be 
offered the chance to ask questions regarding the study procedure prior to proceeding.   
 
Semi-structured qualitative interviews will proceed with participants who give verbal consent. Due to 
the variable nature of response and participant engagement interviews are estimated to last between 
30 minutes and 60 minutes. The interview guide includes planned questions that will be asked to 
every participant. Due to the nature of semi-structured interviews, we may ask appropriate follow-up 
questions or ask participants to elaborate upon statements made.  Study questions include 
appropriate warnings about the sensitivity of questions, where participants may be asked directly 
about negative experiences with healthcare or to elaborate on negative study experiences. As 
appropriate, participants will be reminded that they can take breaks, skip questions they are 
uncomfortable answering, or stop the interview at any time. Interviews will be conducted primarily by 
Ms. Martin as part of a Master's of Genetic Counseling research requirement, with Dr. Mittendorf and 
Mx. Bland to supplement interviews as needed.  
 
Participants who are interviewed will receive a $40 Visa gift card as compensation for their time. Visa 
gift cards will be sent to interviewed participants via email. Individuals who decide to end the interview 
early will still be compensated with the same gift card. 
 
Consent to interview and the interview itself will be recorded on secure Microsoft Teams software, 
which is the preferred secure software of VUMC and transcribed using auto transcription that comes 
pre-installed with Microsoft Teams. Recordings and raw transcripts will be maintained on a secure 
study server within Microsoft OneDrive, with access only available to approved study personnel. 
These transcripts will then be supplemented with manual revisions based on raw recordings (to catch 

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autotranscription errors) and manual redaction of any identifying information – including about 
individuals other than the participant. Because of the sensitive sociopolitical climate for TGSD 
persons, transgender team members (Mx. Bland and Dr. Mittendorf) will review redacted transcripts 
for potentially sensitive data that falls outside the scope of data that is traditionally considered 
identifiable, and may choose to apply stricter data censoring at this time. Deidentified transcripts will 
be uploaded to Dedoose, a cloud-based coding software used to analyze qualitative research. 
 
6. Reporting of Adverse Events or Unanticipated Problems involving Risk to 
Participants or Others 
 
All researchers will report all events that are serious, unexpected, and study-related to the PI by 
phone, fax or email within 24 hours of becoming aware of the event. We will promptly report to the 
IRB any participant complaints about the conduct of any element of the study or concerns about 
potential harms, including copies of any written communication with the participant addressing those 
concerns. Further, all conversations with participants that indicate a level of concern about a study 
component - even if not a complaint - will be documented and distribution of any participant education 
materials in response to such queries will be documented in the participant’s research (REDCap) 
record for the primary study (FOREST). There is the possibility of identifying someone who received 
inappropriate clinical recommendations from MeTree based on their response to the sex question in 
MeTree, which is used in assessing clinical risk. If someone like this is identified, this would be 
reported under the FOREST study protocol, and a new MeTree risk report would be generated. 
 
7. Study Withdrawal/Discontinuation 
Withdrawing participation from interview substudy 
We will continue to utilize the participant interview data in analyses unless the participant asks for the 
data to be withdrawn. If a participant requests that data be withdrawn, raw transcripts and recordings 
will be deleted, as well as any data derived from these that are present in Dedoose or analyses. 
Participants who request that interview data be withdrawn will be notated as actively withdrawn and 
that they requested interview data removal in the tracking database, so that we can maintain 
information about participants. Subjects who wish to withdraw from the main study will be withdrawn 
from FOREST under the main study protocol. 
 
Active Declining Participants 
As noted above, participants can ask to stop the interview at the time, for any reason. If participants 
wish to stop the interview permanently and not reschedule for a follow-up, they will be considered 
withdrawn. Withdrawn participants will follow the withdrawing participation procedure above.  
 
Non-responders (Passive Decline) 
Potential interviewees who agree to interview, but fail to schedule and are unable to be reached or fail 
to attend their interview and are unable to be rescheduled will be considered passive decliners. 
Similarly, if a participant phone call is lost during interview and they are unable to be reached again to 
reschedule the rest of the interview, they will be considered passively withdrawn and will follow the 
procedure above regarding the interview data that was collected until the dropped call. 

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Surveys of declination or withdrawal 
Participants that ask to stop the interview, request or withdraw from the study will be asked why they 
are making this choice.  This information will be tracked in the tracking database for the main 
FOREST study. 
 
Deceased participants 
The study will utilize the data of deceased participants even if they pass before the conclusion of the 
study. 
 
8. Analytic Considerations 
Ms. Martin, Dr. Mittendorf, and Mx. Bland will develop a qualitative codebook using inductive and 
deductive techniques. This codebook will be refined with input from the rest of the FOREST study 
team and Ms. Martin's thesis committee. Dedoose will be used for coding, with Dr. Mittendorf will act 
as a dual coder for Ms. Martin. Mx. Bland or another member of Ms. Martin's committee will serve as 
tiebreaker. Themes will then be identified and findings synthesized. 
 
9. Privacy 
As noted above every effort will be made to remove identifying information from study transcripts and 
participant summaries. There is no intervention in this substudy of FOREST. However, there is the 
possibility that a participant may report emotional distress when recounting experiences with the 
FOREST study or previous personal experiences. In the case of this occurring, we will provide 
participants appropriate numbers to VUMC mental health resources. This referral resource will 
include the VUMC psychology/psychiatry phone number, helplines, and other helpful resources. 
Should this occur, it would also be reported to the IRB. All interview data will be deidentified before 
coding in Dedoose, and only de-identified data will be shared. All identifiable data will be stored on 
secure servers and only accessible to a minimum subset of study personnel. Given the sensitive 
nature of participant gender identities in the current societal climate, additional efforts may be 
undertaken beyond typical requirements under HIPAA to further obscure participant identities or 
sensitive information. Two key personnel on the primary FOREST study, Dr. Mittendorf and Mx. 
Bland, who both have transgender identities and are connected to the Nashville transgender 
community, will guide whether additional data obfuscation beyond HIPAA is necessary to protect 
participants.