Are socio-economic status indicators barriers for enrollment in phase 1 clinical trials?

Abstract

1652 Background: Socio-economic Status (SES) indicators create barriers to access Phase 1 clinical trial (Ph1) enrollment, particularly for underrepresented minorities (URM). However, it remains unclear whether they directly affect enrollment after screening, or represent upstream barriers. We evaluated whether SES indicators impacted the enrollment rate in Ph1. Methods: All patients were screened for Ph1 at Hackensack University Medical Center (2014-2025). Patient ZIP codes were linked to the U.S. Census data (ACS 2018-2022) to derive neighborhood-level SES indicators: median household income (MHI), educational attainment (Bachelor), poverty rate (PR), unemployment rate (UR), and median home value (MHV). SES indicators were compared to national and state census benchmarks. The primary outcome was enrollment rate by SES indicators. We performed univariate analyses (Mann-Whitney U tests, chi-square), stratified analyses by race/ethnicity and gender, temporal trend analysis, and multivariable logistic regression. Results: A total of 1,316 patients were screened for 140 Ph1. Demographics were non-Hispanic White (NHW) 66.2%, Hispanic 19.0%, African American/Black (AA) 7.8%, Asian 6.5%. No SES variable predicted enrollment: median income (enrolled $62,646 vs not-enrolled $61,820, p=0.450), education (38.3% vs 37.9%, p=0.598), poverty (12.9% vs 12.3%, p=0.416), unemployment (6.1% vs 6.0%, p=0.422), home value ($277,461 vs $275,697, p=0.605). SES quartile analysis showed no enrollment gradient (Q1=61.7%, Q2=58.1%, Q3=60.5%, Q4=63.8%; p=0.491). Findings were consistent across all racial/ethnic groups (all p>0.05), see Table 1, gender (all p>0.05), age groups <65 and ≥65 years (all p>0.05), and time periods 2014-2019 vs 2020-2025. When compared to their respective racial/ethnic groups U.S. Census averages, it demonstrated atypical SES profiles: Hispanic patients had higher education (36.6% vs 20.6%), AA showed higher SES across all indicators, and Asians showed lower SES, suggesting regional selection bias in who reaches Ph1 screening. Conclusions: When patients reach Ph1 screening, SES indicators do not predict enrollment, demonstrating that equitable enrollment practices can be achieved at screening. Although there were no visible SES-related barriers at the enrollment point, disparities exist among groups likely suggesting referral patterns prior to screening. Future research should examine how to improve access to Ph1 in URM and upstream inequities. SES analysis stratified by race/ethnicity. Race SES Variable p-value NHW MHI 0.4476 NHW Education 0.4585 NHW PR 0.7483 NHW UR 0.6957 NHW MHV 0.4982 Hispanic MHI 0.8270 Hispanic Education 0.4104 Hispanic PR 0.0646 Hispanic UR 0.2401 Hispanic MHV 0.9677 AA MHI 0.9569 AA Education 0.7355 AA PR 0.9112 AA UR 0.3962 AA MHV 0.3076 Asian MHI 0.2037 Asian Education 0.3200 Asian PR 0.2067 Asian UR 0.0867 Asian MHV 0.1677