Analysis of NCI Community Oncology Research Program (NCORP) clinical trial accrual rates in a comprehensive cancer center and its community affiliate sites.

272 Background: Clinical trials offer innovative regimens for cancer patients while advancing treatment algorithms for future generations. The success of trials is dependent on high enrollment rates and patient participation. This data dissects participation rates among patients with variable diseases and social determinants. Methods: A total of 368 patients in a comprehensive cancer center and its community affiliate sites were screened using NCI’s standardized DCP-001 tool to assess eligibility for NCORP clinical trials. Standardized information was collected about each patient regarding disease status and social determinants. Trial-eligible patients were divided based on their decision to pursue enrollment. T-tests, chi-square tests, and logistic regression were conducted to examine differences between those who did or did not enroll. Analyses were conducted using RStudio, with two-sided tests and a significance level of 0.05. Results: There was a statistically significant difference between the average age of the patients who enrolled in clinical trials versus those who did not (p < 0.001). Pediatric patients ( < 18 years) were more likely to participate than adults (p = 0.013), with 94% pediatric patients enrolled compared to 63% adults. Enrollment was significantly higher among non-rural areas compared to rural (p < 0.001) with 79% non-rural enrolling versus 50% rural. Statistically significant enrollment likelihood increased with education: 78 % of graduate degrees holders enrolled compared to 56% high school educated or lower (p = 0.003). Patients with primary thoracic tumors were significantly more likely to enroll compared to those with tumors at other sites (85% enrollment, p = 0.002). Stage III patients had a 62% less likelihood of enrollment than stage IV patients (p = 0.02). Enrollment did not differ amongst tobacco use, marital status, income, insurance type, payment methods, employment, race, or presence of comorbidities. Conclusions: Associations between each variable and trial participation prompts insight into factors that can be optimized to increase accrual rates among patients less likely to enroll based on certain characteristics. Ultimately, if higher trial accrual rates can be obtained amongst those less likely to enroll, we can more rapidly advance treatments that are applicable to the entire population.