Abstract A001: Tracking the Relationship between Accrual and Comorbidities in Clinical TRrial Enrollment (TRACE)
Authors: Oluloro Ann , Pike Mindy , Moore Adrienne , Luu Tiffany , Jorge Soledad , Doll Kemi M. 
Published: March 2024

Abstract
Background: Clinical trial accrual disparities are pervasive and multifactorial. Prior research shows differential racial enrollment patterns of cancer patients due to comorbidity-based exclusion criteria (CEC). Uterine cancer (UC) has one of the largest racial disparities in incidence and mortality, yet the impact of CEC on accrual of racial minorities into UC trials is unknown. Objective/Hypothesis: To 1) characterize the presenting comorbidity profile of UC patients, by race and 2) use real-world data to quantify expected effects of common CEC on UC trial accrual. We hypothesize that racial minorities with UC have more comorbidities resulting in higher exclusion from trials than Whites. Method: In this observational, cross-sectional study, we used the Vizient ® Clinical Data Base [permission of Vizient Inc. (all rights reserved)] with 8.5 million inpatient and 130 million outpatient encounter level claims annually. We identified individuals ≥18yo with a UC diagnosis, 2002–2021. Demographic variables and comorbidity diagnoses were identified by ICD9/10 codes and used to construct Charlson, Elixhauser, and National Cancer Institute (NCI) comorbidity indices (CI). Individual comorbidity-based and summary theoretical ineligibility rates were calculated, by race, based on a modified set of CEC (Riner et al, JCO 2022). Ineligibility rates were compared between groups and differences assessed with logistic regression using STATA v.18. Result: We identified 384,093 UC patients. 73% were White, 14% Black, 11% unknown race, and 3% Asian. The majority (61%) were of non-Hispanic ethnicity. On average, Blacks had more comorbidities than Whites, Asians, or those of unknown race [1.3 (SD 2), 0.7 (SD 1.6), 0.6 (SD 1.3), 0.9 (SD 1.6), respectively]. For NCI CI, Blacks had the highest CI score (0.8, SD 1.4) while Asians the lowest (0.4, SD 0.9). Whites and those of unknown race had similar scores (0.5, SD 1.1) (all p-values &lt; 0.001). Individual comorbidity prevalence varied significantly by race. Blacks (12%) with UC were more likely to have renal failure compared to Whites (5%). Asians (14%) and Whites (15%) had similar rates of diabetes while Blacks had the highest (24%). Hypertension was higher in Blacks (50%), followed by Whites (33%) then Asians (28%). In simulation analyses, odds of trial exclusion based on comorbidity status were two times higher in Blacks compared to Whites (OR 2.09, 95% CI 2.05-2.13). Those of unknown race had slightly higher odds (OR 1.04, 95% CI 1.02-1.07) and Asians lower odds (OR 0.89, 95% CI 0.86-0.93) of being ineligible relative to Whites. Conclusion: For UC patients, comorbidity prevalence and CI scores varied by race. This results in significant differences in trial eligibility at baseline before any patient engagement. Quantifying the distribution of comorbidities is critical because it allows us to anticipate, statistically, how the accrual of minorities may be hampered by individual CEC. This in turn can support equity efforts of targeted oversampling and strategic site selection to ensure diverse participants.
Citation Format: Ann Oluloro, Mindy Pike, Adrienne Moore, Tiffany Luu, Soledad Jorge, Kemi M. Doll. Tracking the Relationship between Accrual and Comorbidities in Clinical TRrial Enrollment (TRACE) [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A001.