Historically marginalized populations (eg, minoritized racial and ethnic groups, those with lower socioeconomic status, older adults, rural residents, and women) excluded from biomedical research have often been those that carry a disproportionate disease burden. Similarly, these factors also drive disparities in cancer risk factors and outcomes among transgender and gender-diverse populations. For example, in a study by Dr Erik Eckhert and colleagues, patients with breast cancer who are members of sex and gender minority groups experienced delays in diagnosis, declined oncologist-recommended therapies more often, and had a 3-fold higher rate of breast cancer recurrence compared with cisgender heterosexual patients. With trial designs traditionally derived from legacy protocols and expert opinion, this has created long-standing inequities in clinical trial accrual among these populations. Despite efforts to address these inequities, there have been limited gains in diversity in clinical trial representation, including in precision oncology trials.
In 2022, the US Food and Drug Administration (FDA) issued draft guidance and recommendations for including a Race and Ethnicity Diversity Plan in clinical trials. This draft guidance suggests trial sponsors leverage various data sources, including real-world data, to increase diversity within trial populations. In a JAMA Oncology Viewpoint article, Dr Trevor Royce and colleagues discuss the use of real-world data to support the design of more-representative clinical trials with more-inclusive eligibility criteria. These data are widely available, generated and collected during routine healthcare delivery in the form of electronic health records or administrative claims data. The breadth and availability of real-world data make them well positioned to inform inclusive trial eligibility criteria that optimize enrollment and diversity of study populations. Strategic use of real-world data can broaden eligibility criteria and quantify outcomes on eligible patient counts and trial endpoints such as overall survival. Real-world data can also help characterize the differential effects of specific inclusion criteria across racial and ethnic groups, as well as influence trial eligibility criteria modifications for patients with diseases that disproportionately affect a particular group. Critical to this approach is ensuring the quality and relevance of the data source.
Specific to transgender and gender-diverse populations, a review by Dr Alberto Giovanni Leone and colleagues notes that healthcare providers’ lack of knowledge about gender minorities’ health needs represents a major hurdle to cancer prevention, care, and survivorship. Other barriers include discrimination, discomfort caused by gender-labeled oncologic services, stigma, and lack of cultural sensitivity among healthcare providers in the oncology setting. Dr Leone concludes that effective solutions are still needed to ensure that every patient receives optimal care in a person-centric and gender diversity-sensitive environment.
High level
Efforts by trial sponsors to broaden eligibility criteria may not necessarily improve representativeness unless they are specifically designed to prioritize equity. They must also address eligibility criteria that disproportionately and systematically affect historically marginalized patient groups. Dr Royce suggests that trial eligibility criteria prioritize antiracist principles and equitable outcomes on diverse populations. The use of real-world data may permit sensitivity testing across several eligibility criteria and characterize their influence on diversity in clinical trials. Dr Leone and Dr Eckhert suggest that the collection of gender variables is important to performing prognostic and predictive studies and to populating cancer registries. Additionally, strengthening education in transgender and gender-diverse health-related issues through in-person or online training modalities would help address the gap in knowledge among cancer care practitioners in this area.
Ground level
Clinicians can help support increased diversity in clinical trials by recommending trial participation to patients from historically marginalized populations when appropriate. To better support the transgender and gender-diverse populations, a comprehensive approach should include complementary medical, legal, and psychosocial services to address key socioeconomic determinants of health. Recommendations for these individuals should be driven by anatomic characteristics, also considering lifestyle factors, with an emphasis on shared decision-making.
