Association Between Comorbidity and Clinical Trial Enrollment for Patients With Uterine Cancer

To characterize the presenting comorbidity profile of patients with uterine cancer by race and ethnicity and use real-world data to quantify expected effects of common comorbidity eligibility criteria on uterine cancer trial accrual.

This observational, cross-sectional study used the Vizient Clinical Data Base to identify individuals aged 18 years or older with a uterine cancer diagnosis from 2002 to 2021. Demographic variables and comorbidity diagnoses were identified by International Classification of Diseases, Ninth and Tenth Revision codes and used to construct Charlson, Elixhauser, and National Cancer Institute comorbidity indices. Summary theoretical ineligibility rates were calculated by race based on a modified set of comorbidity-eligibility criteria. Ineligibility rates were compared between groups and differences assessed with logistic regression.

We identified 384,093 patients with uterine cancer; 70.0% of the patients were non-Hispanic White, 13.4% were non-Hispanic Black, 7.1% were of unknown race, and 2.8% were non-Hispanic Asian. Across all comorbidity indices, non-Hispanic Black individuals persistently had the highest scores among all racial groups. Comorbidity prevalence varied significantly by race. Non-Hispanic Black individuals had the highest rates of renal failure (11.6%), diabetes (23.4%), and hypertension (49.8%) compared with non-Hispanic White and non-Hispanic Asian individuals. In modeling analyses, non-Hispanic Black individuals had twofold higher odds of trial exclusion based on comorbidities than non-Hispanic White individuals (adjusted odds ratio [aOR] 2.06; 95% CI, 2.02-2.10). Those of unknown race had slightly higher odds (aOR 1.02; 95% CI, 0.99-1.05) and non-Hispanic Asians slightly lower odds (aOR 0.98; 95% CI, 0.94-1.02) of being ineligible relative to non-Hispanic White individuals.

For patients with uterine cancer, comorbidity prevalence and comorbidity index scores varied by race. This results in differences in trial eligibility at baseline before any patient engagement. Quantifying the distribution of comorbidities is critical because it allows us to statistically anticipate how individual comorbidity eligibility criteria may hamper the accrual of patients from minoritized groups. This, in turn, can support equity efforts to plan trial eligibility criteria and targeted recruitment.