Paper Details

ABSTRACT

Introduction: Diffuse Large B-cell Lymphoma (DLBCL) has high response rates and overall survival (OS) when managed with combination chemotherapy, however, notable racial and socioeconomic disparities persist (Han X, et al., Cancer 2014). Prior studies have shown that socioeconomic factors beyond insurance status such as zip code and education level are strong predictors of OS (Han X, et al., Cancer 2014). Here we present preliminary data on patients diagnosed with DLBCL and treated at a community hospital in South Florida, to determine the frequency of delays between cycle (C) 1 and C2 and identify what socioeconomic factors contributed to this delay.

Methods: We performed a retrospective analysis of patients ≥18 years old diagnosed with DLBCL between 2021 and 2023. Eligible patients were diagnosed in the hospital and received at least one inpatient cycle of R-CHOP or R-EPOCH. Baseline socioeconomic variables including race, language, housing, education level, employment status, income, established primary care provider (PCP), immigration status, and transportation access were collected. Treatment delays were assessed and defined as > 21 days between the administration of C1 and C2 of chemotherapy. Socioeconomic subgroups were compared using Fisher’s exact test to evaluate the association of individual socioeconomic factors with delays in care.

Results: 30 patients with DLBCL were identified. The average age was 60 years (range 41-81) and the majority of patients had Stage IV disease (73%). The most common primary language was Spanish (56%) and 20% of patients were undocumented immigrants or had unclear citizenship status. The majority of patients were male (56%), white (63%), and Hispanic (63%), although a significant portion were black (30%). 10% were unhoused, 20% had less than high school degree, 73% were unemployed at diagnosis, 33% had income < $30k USD, 33% had no PCP, and 3% lacked transportation.

Out of 30 patients, 70% of patients (21/30) received C2 of therapy. Of the remaining patients, 7 died after C1 (23%), and 2 were lost to follow up. Patients who died after C1 were older (66 vs 58 years old) than those that completed C2 (P value = 0.38).

The average time between C1 and C2 was 35.6 days (IQR 21-42), with 61% of patients (13/21) experiencing a delay between C1 and C2. Delays in care were most commonly due to medical complications (4/21), admission delays for R-EPOCH (4/21), insurance issues (1/21), or issues with adhering to treatment (1/21). Lack of access to transportation (mean 148 days), less than high school education (mean 55 days), average salary of $58-94k USD (mean 43 days), white race (mean 42 days), and unemployed at diagnosis (mean 41 days) had the highest delays between C1 and C2, however, they were not statistically significant in predicting delays in treatment.

Conclusion: In this single-center retrospective study of patients with DLBCL treated at a community safety-net hospital, preliminary findings show that a significant portion of patients experienced a delay in care between C1-2. Although no individual socioeconomic factor was significantly associated with treatment delays, transportation access, lower education level, employment status, and race had longer delays between C1 and C2. The small sample size and high early mortality rate limit the power to detect differences between subgroups. However, these preliminary findings highlight the complexity of this population and support the need for larger studies to better understand the relationship between socioeconomic factors and delays in care and outcomes, with the goal of developing targeted interventions to counteract these disparities and equalize care.