For the findings to be usable, healthcare research clinical trials must accrue participants that accurately represent the general population to which the study applies. But that’s easier said than done. During a session on April 27, 2021, for the 46th Annual ONS Congress™, two oncology nurse scientists shared strategies that other researchers can use to overcome disparities in clinical trial study populations.
Adjust Methods for Social Determinants of Health
Usha Menon, PhD, RN, FAAN, from the University of South Florida (USF) College of Nursing and USF Health, said that researchers must look more broadly than race or ethnicity to consider how poverty, and regional or geographic resources, and social determinants of health affect clinical trial disparities.
People living in persistent poverty are more likely to die from cancer than people in other counties, she said. An area living in persistent poverty is defined as 20% of the population living below the federal poverty level since 1980. And that risk than that for people who live in areas with current— but not persistent—poverty, Menon said. She challenged researchers to build trust with communities experiencing persistent poverty and include them and their residents in future studies.
She also said that researchers must ensure their enrollment methods are not based on traditional or prevailing paradigms. People have different ways of working, playing, eating, and living, depending on their background and lifestyle, and researchers should adjust their approaches for various ideologies. Menon said there are many models and theories for support.
Safely Involve Older Adults
Ashley Leak Bryant, PhD, RN-BC, OCN®, FAAN, from the University of North Carolina at Chapel Hill School of Nursing and Lineberger Comprehensive Cancer Center, discussed the inclusion of older adult patients and their caregivers in research and clinical trials. Although those groups may be underrepresented because of narrow eligibility criteria, concern for treatment toxicities, and lack of access to cancer centers with clinical trials, they are significant users of cancer treatments and must be represented in trials to generate evidence for care.
“Older adults remain vastly underrepresented in the research that sets the standards for cancer treatment and behavioral research,” Bryant said. “Consequently, most of what is known about cancer therapies is based on clinical trials conducted in younger, healthier patients, and non-racially and -ethnically diverse populations.”
Older adult patients may be excluded from trials because of eligibility criteria that limits patients with comorbidities, who are frail, or who have cognitive impairments. The difficulty or inefficiency of investing time into enrolling older adults can discourage oncologists from recommending clinical trials. Researchers need to broaden accrual by optimizing trial designs for increased participation.
Bryant said nurse scientists must engage key stakeholders, including patient advocates and community-based clinicians, to improve clinical trial participation.
“These discussions can inform protocol design and ensure participants are more representative of the patient populations beyond the academic setting. We must leverage leadership and resources that will maximize inclusion,” she said.
She shared strategies for enrolling more older adults:
- Inform patients that their oncologist, nurse practitioner, or physician assistant referred them to the study.
- Maximize time that can be used for recruiting patients, such as during rounds or in the afternoon in a hospital setting or between appointments in a clinical setting.
- Let patients know that a summary of findings will be shared with all study participants and caregivers.
- Be kind and compassionate and thank the patient and caregiver for participating.
- Provide incentives at enrollment and during study timepoints, such as gas cards, parking vouchers, or cash. Ask the patient advocate what would be preferred for this population.
Bryant also emphasized the importance of capturing the reasons for attrition and dropout to inform future approaches.