Background: Socioeconomic disadvantage, as measured by the Area Deprivation Index (ADI), is associated with adverse health outcomes across cancer types. However, its impact on outcomes among patients receiving chimeric antigen receptor T-cell therapy (CART) remains understudied. We examined the association between ADI and survival outcomes, treatment characteristics, and patient demographics among CART recipients.

Methods: We conducted a retrospective cohort study of 391 patients with relapsed/refractory large B-cell lymphoma (R/R LBCL) treated with CAR T-cell therapy between 2015-2024 across 12 academic cancer centers. ADI, a widely cited measure of neighborhood socioeconomic disadvantage developed by the University of Wisconsin, was linked to patient ZIP code at the time of diagnosis using the 2020 national percentile rankings. ADI was categorized as a binary variable, with high deprivation defined as the top 25% most socioeconomically disadvantaged scores. Differences in demographic and treatment characteristics between ADI groups were assessed using Pearson's chi-squared test, Fisher's exact test, and Wilcoxon rank-sum test. Associations between ADI and survival were examined using Kaplan-Meier curves, log-rank tests, and Cox proportional hazards models adjusted for demographic, clinical, and treatment-related covariates. All covariates were retained in the models regardless of statistical significance, based on clinical relevance and prior literature.

Results: There was a total of 97 patients with high ADI. These patients were more likely to be non-Hispanic Black (8.3% vs. 4.8%, p=0.09), to have undergone autologous stem cell transplantation before CART (28% vs. 13%, p=0.001), and to experience travel times of two or more hours to their treatment center (67% vs. 25%, p<0.001). High ADI patients also had lower CART complete response rates (51% vs. 66%, p=0.006), experienced a longer time from cell collection to CART infusion (42 vs. 37 days, p=0.007), and were more likely to receive Kymriah (33% vs. 12%) and less likely to receive Breyanzi (10% vs. 26%, p<0.001). There were no significant differences between high ADI vs low ADI across sex, age, insurance type, Eastern Cooperative Oncology Group performance (ECOG) status, disease stage, extranodal involvement, histologic subtype, cell of origin, double-hit lymphoma (DHL), prior bendamustine use, clinical trial participation, neurotoxicity or cytokine release syndrome, use of tocilizumab, prior treatment lines, time from relapse with last prior therapy to CART infusion, or time from CART relapse to subsequent therapy.

Patients in areas of higher deprivation experienced inferior survival, with lower median progression-free survival (mPFS) (7.75 vs. 13.17 months, p=0.2) and overall survival (OS) (28.52 months vs. not reached (NR), p=0.019). High ADI demonstrated inferior mPFS among the subgroups of patients age > 60 years (7.29 vs. 28.45 months, p=0.001), DHL (5.95 vs. 17.02 months, p=0.4), and primary refractory disease (3.75 vs. 7.23 months, p=0.12). OS showed similar outcomes with significant differences for age > 60 years (25.76 vs. NR, p=0.009) and primary refractory disease (18.07 vs. NR, months, p=0.009).

In multivariable analysis for PFS, high ADI was not significantly associated with progression (HR 1.15, p=0.5). However, a drive time over 2 hours increased the risk of progression by 51% compared to patients with a drive time under 1 hour (HR 1.51, p=0.042). For OS, patients residing in high ADI areas experienced a 65% increased risk of death (HR 1.65, p=0.027), and those with an ECOG of 2-4 had more than double the risk of death (HR 2.26, p=0.014) relative to those with better functional status (ECOG 0-1).

Conclusion: Our data demonstrate that socioeconomic disadvantage, as represented by high deprivation across the country, greatly impacts the survival of patients with R/R LBCL receiving CART. Given that our data exclude those not referred for CART, our findings may underestimate the negative impact of socioeconomic disadvantage on survival. Improving access to care through initiatives such as transportation assistance, lodging support, or the expansion of local services may help mitigate the negative impact of long travel times. Screening for social determinants of health during intake and embedding patient navigator support can further reduce the burden of socioeconomic disadvantage by identifying and addressing barriers early in the treatment process.

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2025
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