How exclusion criteria can hinder eligibility for lung cancer studies among different racial and ethnic groups.

The extent to which protocol eligibility criteria contribute to the underrepresentation of racial and ethnic minority populations - including Black, Asian, and Latino Americans - in lung cancer clinical trials remains poorly characterized. This study quantifies the likelihood of clinical trial exclusion attributable to comorbid conditions across racial and ethnic groups among patients with lung cancer. Data were drawn from 1,134 lung cancer clinical trials registered on ClinicalTrials.gov with start dates between January 2014 and December 2024, and patient comorbidity data were obtained from electronic medical records (EMR) at a large urban academic medical center in the Northeast United States. Data analysis was conducted between February and May 2025. Eligibility for trial enrollment was assessed by mapping patient comorbidity profiles against study exclusion criteria; binary logistic regression was used to estimate the likelihood of exclusion by race and ethnicity, with sex and median household income included as covariates. The analytic sample comprised 4,096 patients with lung cancer (73.6% White, 12.8% Asian or Pacific Islander, 3.3% Black or African American, and 1.8% Hispanic/Latino). Compared to White American patients, Asian American and Pacific Islander (AAPI) patients and Black or African American patients were 1.8 times (OR: 1.8, 95% CI: 1.03-3.03) and 1.6 times (OR: 1.6, 95% CI: 1.01-2.48) more likely to be excluded from clinical trials based on their comorbidities, respectively. These findings indicate that standard protocol exclusion criteria may disproportionately screen out racial and ethnic minority patients, particularly Black/African American and AAPI individuals, and may represent a structural contributor to their underrepresentation in lung cancer research. Revising eligibility criteria to better reflect real-world comorbidity burdens could improve the inclusivity and generalizability of lung cancer clinical trials.