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Background: To explore the association between ethnicity, as a proxy for language, and participation in clinical trials (CT) conducted by Principal Investigators (PI) who speak one or more language in addition to English. Methods: This retrospective, descriptive study utilized CT participant demographic data extracted from the largest Midwestern non-profit healthcare system between January 1, 2019 and 12/31/2021. The CT participant sample (N = 4308) was divided for comparison: CT Participants of Hispanic or Latino Origin (N = 254; 5.90 %) and CT Participants of Non-Hispanic or Latino Origin (N = 4054; 94.10 %). Logistic regressions were performed to generate the crude and adjusted odds of patients of Hispanic or Latino origin participating in CTs conducted by PIs who speak another language in addition to English. Results: Crude analysis revealed that patients of Hispanic or Latino ethnicity had 2.04 (1.58, 2.64) times greater odds of participating in CTs conducted by PIs who speak another language than English (<0.0001), which increased to 2.67 (1.97, 3.62) times greater odds after adjusting for sex, race, age and insurance (p < 0.0001). Conclusions: Overall findings indicate that patients of Hispanic or Latino ethnicity, who are more likely to speak Spanish, have greater odds of participating in CTs conducted by PIs who speak another language beyond English. This may imply that cultural sensitivity at the top of a CT study team, as likely to be demonstrated by PIs who speak another language beyond English, may be an important contributor to reducing ethnicity- and language-based barriers to diversity in CTs and a relationship worth exploring further.
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Background: Representativeness in clinical trials (CT) serves as a metric of access to healthcare and reflects differences that may determine differential efficacy of medical interventions; thus, quantifying representativeness in CT participation is critical. Methods: This retrospective, descriptive study utilized patient demographic data extracted from the largest Midwestern non-profit healthcare system. Using data between January 1, 2019 and December 31, 2021, a CT Participant Sample of 4,537 system patients who were active CT participants was compared to a CT Patient Population of 195,726 system patients receiving care by the PI of active CTs, which represented the target population. Chi-square goodness-of-fit tests were used to test differences in distributions of demographic variables between groups, indicating disparity in CT participation. Two metrics adapted from literature - participation incidence disparity (PID) and participation incidence ratio (PIR) - were calculated to quantify absolute and relative disparity in representativeness proportions, respectively. Descriptive approaches to assessing representativeness are also provided. Results: Results showed significant differences by race/ethnicity (χ2 = 50.64; p < 0.0001), age categories (χ2 = 56.64; p < 0.0001), and insurance (χ2 = 41.29; p < 0.0001). PID and PIR metrics revealed reduced CT participation among non-White racial/ethnic groups and increased CT participation among White Non-Hispanic patients. Further, CT participants ≥80 or Worker's Compensation were underrepresented while those with Self-Pay insurance were overrepresented as CT participants. Conclusions: Despite progress, continued efforts to not only enroll participants into CTs that are representative of the healthcare system and region, but also to better assess representativeness quantitatively are still needed.
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INTRODUCTION: Individual demographic data and socioeconomic status (SES) factors from Census block group data may help define groups with disadvantaged access to clinical trials. METHODS: Individual demographic data from the Aurora Cancer Registry and SES factors corresponding to the Census block group of the patient's address were studied for a six-year period ending July 31, 2019. RESULTS: The final study cohort included 39,968 patients (enrolled = 772, and not enrolled = 39,196). In univariate analysis, significantly fewer patients older than age 65 (p < 0.001) and fewer men (p < 0.001) were enrolled in clinical trials. Socioeconomic factors found to be significant during univariate analysis included: low household income (p < 0.001), percentage below the poverty line (p < 0.001), low percentage home ownership (p = 0.006), unemployment (p = 0.003), absence of a college degree (p = 0.037) and absence of a high school degree (p = 0.007). In multivariate analysis, patients older than age 65 were less likely to participate in a trial (odds ratio 0.574, p < 0.001) and men were less likely to participate (odds ratio = 0.703, p < 0.001). Only 1.4% of the variance in clinical trial participation was accounted for demographic and SES factors. CONCLUSIONS: The only groups with disadvantaged access to clinical trials in our institution were the elderly and men. Whether demographic or SES factors are related to accrual rates of clinical trials in other geographic regions or in other types of research studies warrants further investigation.