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

## TL;DR

This study shows that lung cancer clinical trials may unfairly exclude more Black and Asian American patients due to strict eligibility rules based on comorbidities.

## Contribution

The study quantifies how exclusion criteria in lung cancer trials disproportionately affect racial and ethnic minorities.

## Key findings

- AAPI and Black patients were 1.8 and 1.6 times more likely to be excluded than White patients due to comorbidities.
- Exclusion criteria may contribute to underrepresentation of minorities in lung cancer research.
- Revising eligibility rules could improve inclusivity in clinical trials.

## Abstract

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.

The development of treatments for patients with lung cancer relies on the enrollment of patients in clinical trials; however, racial and ethnic minority patients have remained underrepresented in these studies, raising questions about the efficacy and safety of treatments for underenrolled patient populations. While several factors contribute to the under enrollment, one factor that may hinder accessibility are stringent protocol exclusion criteria. For example, certain medical conditions that have a higher incidence among racial and ethnic minority patients may be listed as exclusion criteria, preventing patients from these communities from qualifying for lung cancer studies. The extent to which medical conditions listed under exclusion criteria can impede eligibility for patients into lung cancer clinical trials remains largely unknown. To fill this gap, we used patient electronic medical records (EMR) and mapped them to exclusion criteria taken from lung cancer clinical trial studies registered on ClinicalTrials.gov. We then quantified the odds that a patient would qualify for a lung cancer study based on their medical condition. Results showed that Asian American and Pacific Islander (AAPI) patients and Black or African American patients were significantly more likely to be excluded from clinical trials than White American patients based on their comorbidities. We discuss implications of our study results, adding to the existing research on reducing clinical trial protocol complexity to make lung cancer studies more accessible to patients.