Barriers to Investigator-Initiated Clinical Trial Enrollment in Frontline Large B-Cell Lymphoma

Clin Lymphoma Myeloma Leuk. 2025 Nov 4:S2152-2650(25)04270-3. doi: 10.1016/j.clml.2025.11.002. Online ahead of print.

ABSTRACT

BACKGROUND: Frontline therapy fails to cure ∼ 25% of patients with large B-cell lymphoma (LBCL), underscoring the need for clinical trials to improve outcomes. However, enrollment remains limited by logistical and structural barriers. Investigator-initiated trials (IITs) at our center enroll patients 5 to 10 times faster than industry-sponsored trials, yet the influence of geography and socioeconomic status on participation remains poorly understood.

METHODS: We retrospectively reviewed adults with newly diagnosed large B-cell lymphoma (LBCL) referred to Fred Hutchinson Cancer Center (FHCC) between October 2022 and June 2024. Patients were prescreened by a clinical research nurse and investigators for frontline IIT eligibility. Demographic, geographic, and socioeconomic data were collected, including sex, race, ethnicity, distance from FHCC, area deprivation index, insurance, and interpreter need. Logistic and elastic net regression were used to evaluate predictors of trial enrollment. Trial-ineligible patients were analyzed descriptively.

RESULTS: Of 153 patients, 68 (44%) were trial-eligible; 24 (35%) enrolled. Enrolled patients lived closer to FHCC (median 15 vs. 50 miles; P = .00015) and had lower ADI scores (median 8 vs. 21; P = .006) than non-enrolled eligible patients. In univariate analysis, both distance and ADI were associated with enrollment; in multivariable stepwise regression, only distance remained significant. Elastic net regression identified both distance and ADI as frequently selected predictors. Among 85 trial-ineligible patients, 61% had already initiated treatment; these patients also lived farther away and in more deprived areas.

CONCLUSION: Geographic distance and neighborhood deprivation significantly influenced trial enrollment, even in investigator-initiated trials (IITs). Decentralized trial models, telemedicine triage, and system-level interventions are needed to reduce these inequities.

PMID:41285650 | DOI:10.1016/j.clml.2025.11.002