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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.
