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5096 Enrollment in Clinical Trials Demonstrates Benefit for Low Income DLBCL Patients; A Retrospective National Cancer Database (NCDB) Analysis

Program: Oral and Poster Abstracts
Session: 906. Outcomes Research: Lymphoid Malignancies Excluding Plasma Cell Disorders: Poster III
Hematology Disease Topics & Pathways:
Adult, Clinical Practice (Health Services and Quality), Diversity, Equity, and Inclusion (DEI), Human
Monday, December 9, 2024, 6:00 PM-8:00 PM

William Schwartzman, MD1, Ang Gao, MS2*, Chul Ahn, PhD2*, Heather R Wolfe, MD3,4*, Praveen Ramakrishnan Geethakumari, MD, MS4, Farrukh T. Awan, MD5 and Elif Yilmaz, MD6

1Harold C. Simmons Comprehensive Cancer Center, UT Southwestern, Irving, TX
2Peter O’Donnell Jr. School of Public Health, UT Southwestern Medical Center, Dallas, TX
3University of Texas Southwestern Medical Center, Dallas, TX
4Section of Hematological Malignancies and Cellular Therapy, Harold C. Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX
5Southwestern Medical Center, Harold C. Simmons Comprehensive Cancer Center, The University of Texas, Dallas, TX
6Hematologic Malignancies and Cellular Therapy, University of Texas Southwestern Medical Center, Dallas, TX

Background: Diffuse Large B-Cell Lymphoma (DLBCL) is the most common type of Non-Hodgkin Lymphoma and is curable in 60-70% of newly diagnosed cases. Despite the steady decline in DLBCL mortality over the last 3 decades, significant disparities remain among patients (pts) due to differences in socioeconomic factors such as income, marital status, insurance status and treatment facility that affect overall survival. Low-income pts face barriers to accessing high quality care resulting in poorer treatment outcomes. Clinical trials offer access to therapies and comprehensive care that might otherwise be unavailable to low-income pts, potentially assisting in bridging the outcome gap. In this retrospective study, we leveraged the NCDB to illustrate the impact of baseline demographics and clinical factors on enrollment in clinical trials and the effect of clinical trial enrollment on various patient populations with DLBCL.

Methods: A retrospective cohort study was performed utilizing the latest version NCDB, a hospital-based cancer registry. Adult pts with DLBCL diagnosed between 01/2010 and 12/2020 were included in the analyses. Pts with HIV infection and those who did not receive any systemic treatment as part of their first line (1L) therapy were excluded. A propensity score (PS) matched cohort was created using 1:2 PS matching based on age, disease stage, and diagnosis year. Demographics and clinical characteristics at diagnosis, including age, sex, race/ethnicity, insurance type, median income, residence (urban/rural), Charlson Deyo comorbidity score (CDCS), stage, International Prognostic Index (IPI) score and time to systemic therapy initiation were compared. Pts diagnosed between 01/2016 and 12/2020 were categorized into lower and higher income groups using an annual income threshold of $74,603, based on the 2020 American Community Survey data. Chi-square tests were used to compare categorical variables between two cohorts. A stepwise Cox proportional hazards model was used to assess the association between baseline variables and overall survival (OS). The Kaplan Meier method was used to estimate the median OS, and log-rank tests to compare the OS between two cohorts.

Results: Of 306,681 newly diagnosed DLBCL pts, only 710 pts (0.23%) were enrolled in clinical trials for their 1L therapy. Among the 107,918 pts (37.9%) treated at academic centers, 448 (0.42%) participated in clinical trials. A total of 1,968 pts were included in the 1:2 PS-matched cohorts, with 656 pts receiving treatment in clinical trials and 1,312 receiving systemic treatment outside of a clinical trial setting (SOC). Pts enrolled in clinical trials were more likely to be treated at academic centers (75.3% vs 39.5%), have private insurance (49.2% vs 45.5%), be in the higher income group (51.6% vs 36.5%), have CDCS of 0 (79.6% vs 75.9%), and have longer median time to systemic therapy from diagnosis (46 days vs 35.5 days) compared to pts receiving SOC. Other variables, including median age, sex, race/ethnicity, residence, stage, and IPI score at diagnosis were similar between the 2 cohorts.

The median OS was 123.9 months (95% CI: 111.1 - not reached [NR]) for pts enrolled in clinical trials compared to 140.8 months (95% CI: 107.9 - NR) in pts receiving SOC with a hazard ratio (HR) of 1.55 (95% CI: 0.98 - 1.36; p=0.0879), indicating no statistical difference. However, pts in the lower income group had better OS when they enrolled in clinical trials compared to receiving SOC (NR vs 99.9 months respectively; p=0.0117). In contrast, pts in the higher income group had similar OS when enrolled in clinical trials vs receiving SOC (NR vs NR; p = 0.2603).

Conclusion: Although overall enrollment in clinical trials for 1L treatment of DLBCL was low, pts from higher income groups and those with private insurance were more likely to participate in clinical trials, often receiving care at academic centers. Clinical trial enrollment significantly improved OS in lower income pts compared to similar survival seen in higher income pts, whether they enrolled in clinical trials or received SOC. These results highlight the need for policies and interventions to increase clinical trial participation in low income DLBCL pts as a strategy to mitigate outcome disparities.

Disclosures: Wolfe: Curio Sciences: Other: Paid Lecture. Ramakrishnan Geethakumari: Bristol Myers Squibb: Consultancy; Kite Pharma: Consultancy; ADC therapeutics: Membership on an entity's Board of Directors or advisory committees; Cellectar Biosciences: Membership on an entity's Board of Directors or advisory committees; Ono Pharma: Membership on an entity's Board of Directors or advisory committees; Ipsen Biopharma: Membership on an entity's Board of Directors or advisory committees; Regeneron Pharma: Membership on an entity's Board of Directors or advisory committees. Awan: AbbVie/Pharmacyclics: Consultancy, Research Funding; AstraZeneca: Consultancy; BMS: Consultancy; Adaptive Biotechnologies: Consultancy; Dava Oncology: Consultancy; ADC Therapeutics: Consultancy; Genmab: Consultancy; Incyte: Consultancy; Loxo Oncology: Consultancy; BeiGene: Consultancy. Yilmaz: Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees.

*signifies non-member of ASH