Survey examines trial enrollment motivation among diverse populations.
The life sciences industry is collectively recommitted to better addressing challenges to diversity and inclusion in clinical trials, especially among traditionally underserved populations. What we know is that there is no singular formula to effectively resolve this longstanding issue. As such, clinical trial sponsors, their contract research organization (CRO) partners, and other industry stakeholders are recognizing the importance of approaching each trial program with a deliberate focus on diversity goals during trial design and planning activities.
In that same thought, it is important to ask, “Does motivation to enroll in a study vary by race and ethnicity?” And if yes, how can sponsors plan for those differences to ensure heightened enrollment but also an enhanced patient experience, which is at the heart of it all?
To take a deeper look into trial enrollment and individual reasons for participation, IQVIA conducted a survey among 1,693 US adult participants of all ages and medical statuses who self-identified their race and ethnicity. Roughly equivalent to the US population, the race identified by respondents were white (71%), Black/African American (16%), Asian (6%), American Indian/Alaskan Native (3%), Hawaiian/Pacific Islander (0.5%), or “other race” (4%). In addition, 11% of respondents self-identified their ethnicity as Hispanic. Respondents were questioned about trial design elements that may affect their willingness to enroll. It is through qualitative data such as these that sponsors and study teams can better ensure future trial protocols consider the potential impact on participants early in the process.
Overall, the survey was designed to measure:
We first screened out respondents who answered they were “not at all willing” to ever consider participating in a clinical trial. From there, remaining participants were asked whether they would be “extremely willing,” “very willing,” “moderately willing,” “slightly willing,” or “not at all willing” to participate in a clinical trial when presented with 42 questions to assess the impact of various trial protocol design elements.
From a topline view of feedback, the survey indicated that 73% of all respondents were extremely or very willing to participate in a trial (see Figure 1 below). Hispanic respondents were most willing, with 85% extremely or very willing, and 60% of those extremely willing. However, trial design had a greater influence on their level of interest than other groups. Alternatively, while Black/African American respondents were more willing than other races to participate, with 46% noting they were extremely willing, their interest was less affected by trial design.
Confirming this interest is an important first step in actively listening to patients and understanding how to heighten their experience. However, there were notable nuances for sponsors to consider regarding how trial design affects this initial willingness to participate.
To understand how to approach various community groups regarding trial participation, it was vital to also examine what, if any, trial design elements influenced willingness to participate for each race and ethnicity.
Survey insights helped determine what specific trial components were potential hindrances to participation per race and ethnicity (see sidebar).
For example, as the industry has taken a closer look at the patient experience, it is evident that logistical burdens can make patient recruitment difficult. The survey found that the length of time required at clinic visits was one of the top influencers across all respondent groups. However, for Black/African American respondents, visit schedule elements such as visit lengths and even required overnight stays, did not influence their willingness as much compared to other groups.
Procedures a participant must undergo during the trial are another area that may affect patient recruitment. The survey findings indicated that seven noninvasive imaging procedures, such as computed tomography (CT scans) and positron emission tomography (PET scans), did not affect willingness for most respondents, but Asian and Hispanic respondents were more likely to indicate some of these procedures would influence their willingness.
Frequency of blood draws for most survey respondents was correlated with their willingness to participate. As the percentage of trial visits that contain blood draws increased, the negative effect on willingness to participate also increased. However, for Hispanic respondents, not only was there a higher difference from the overall respondents in willingness when blood draws were at 100% of trial visits, but the negative effect on willingness also remained at the same high level even as frequency of visits requiring blood draws decreased.
To make tangible progress in improving sufficient representation in clinical trials, it is critical to remove assumptions regarding lack of willingness and the notion that focusing on diversity adds time and cost to drug development. As these groups are interested in participating in clinical trials, both for themselves and to represent “patients like me,” how can we make trial designs more attractive to them? Fine-tuning trial design and operations based on patient feedback can be one critical piece of the puzzle toward measurable progress in diversity and inclusion enrollment success.
Actively listening to patients via survey feedback and analysis, social listening, patient focus groups, desktop research, and more can provide a solid understanding of patient burden as well as insights into how patients feel about their disease and related treatment options.
Translating qualitative differences in perception of patient burden by race and ethnicity into a quantitative algorithm using data-driven methodologies allows sponsors to calculate and compare the burden of their protocol. Integrating the perspectives of diverse populations during the trial planning stages can help validate the study design plan and make adjustments earlier to help increase enrollment potential and reduce potential protocol amendments.
Denise Messer, director, design analytics, Applied Data Science Center, IQVIA