Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study.

A person's phenotypic sex (i.e., endogenous expression of primary, secondary, and endocrinological sex characteristics) can impact crucial aspects of genetic assessment and resulting clinical care recommendations. In studies with genetics components, it is critical to collect phenotypic sex, information about current organ/tissue inventory and hormonal milieu, and gender identity. If researchers do not carefully construct data models, transgender, gender diverse, and sex diverse (TGSD) individuals may be given inappropriate care recommendations and/or be subjected to misgendering, inflicting medical and psychosocial harms. The recognized need for an inclusive care experience should not be limited to clinical practice but should extend to the research setting, where researchers must build an inclusive experience for TGSD participants. Here, we review three TGSD participants in the Family History and Cancer Risk Study (FOREST) to critically evaluate sex- and gender-related survey measures and associated data models in a study seeking to identify patients at risk for hereditary cancer syndromes. Furthermore, we leverage these participants' responses to sex- and gender identity-related questions in FOREST to inform needed changes to the FOREST data model and to make recommendations for TGSD-inclusive genetics research design, data models, and processes.

Family history and cancer risk study (FOREST): A clinical trial assessing electronic patient-directed family history input for identifying patients at risk of hereditary cancer.

BACKGROUND: Hereditary cancer syndromes cause a high lifetime risk of early, aggressive cancers. Early recognition of individuals at risk can allow risk-reducing interventions that improve morbidity and mortality. Family health history applications that gather data directly from patients could alleviate barriers to risk assessment in the clinical appointment, such as lack of provider knowledge of genetics guidelines and limited time in the clinical appointment. New approaches allow linking these applications to patient health portals and their electronic health records (EHRs), offering an end-to-end solution for patient-input family history information and risk result clinical decision support for their provider. METHODS: We describe the design of the first large-scale evaluation of an EHR-integrable, patient-facing family history software platform based on the Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources (SMART on FHIR) standard. In our study, we leverage an established implementation science framework to evaluate the success of our model to facilitate scalable, systematic risk assessment for hereditary cancers in diverse clinical environments in a large pragmatic study at two sites. We will also evaluate the success of the approach to improve the efficiency of downstream genetic counseling resulting from pre-counseling pedigree generation. CONCLUSIONS: Our research study will provide evidence regarding a new care delivery model that is scalable and sustainable for a variety of medical centers and clinics. TRIAL REGISTRATION: This study was registered on ClinicalTrials.gov under NCT05079334 on 15 October 2021.