Background For patients with hematologic malignancies (diffuse large B-cell lymphoma [DLBCL], multiple myeloma [MM], and chronic myeloid leukemia [CML]), delays in treatment may lead to worsened clinical outcomes due to unacceptable morbidity that occurs prior to treatment. We hypothesize that patients with hematologic malignancies who have significant financial hardship at diagnosis experience delayed time to treatment initiation (TTI).

Methods We performed a retrospective analysis of patients with DLBCL, MM, and CML identified from the Fred Hutchinson Cancer Center (FHCC) Data Repository, which links Western Washington SEER records, insurance claims, and TransUnion credit reports. Patients were included in the analysis if they were diagnosed between 2012 and 2021 and received chemotherapy or targeted therapy within 1 year from diagnosis and had a credit report within 50 days of diagnosis. Credit records were queried for evidence of adverse financial events (AFEs; foreclosures, repossessions, liens, charge-offs, collections, or past due debt) prior to diagnosis. We calculated the TTI from the date of diagnosis to the first claim for treatment. We performed bivariate nonparametric tests and multivariable least squares linear regression, with TTI as the dependent outcome and AFE as the key predictor, adjusting for age, sex, race, insurance type, and geographic socioeconomic disparity by Area Deprivation Index. Based on literature review and expert consultation, we also identified patients with TTI greater than 60 days, which was designated as a prolonged treatment start. We performed bivariate tests and multivariable logistic regression on this categorical outcome in a similar manner.

Results We identified 1110 patients, 531 with DLBCL, 463 with MM, and 116 with CML. Patients averaged 69 years old (median), were 57% male, 88% white, and 30% resided in areas of higher socioeconomic disparity. All patients had health insurance, with 47% having Medicare, 27% commercial, 10% Medicaid, and 15% multiple forms of insurance, respectively.

The prevalence of AFEs at diagnosis was 24%. Patients with AFEs were more likely to be younger (61 vs. 69 years, P < 0.001), non-white (33% vs. 23%, P = 0.01), have CML (23% DLBCL, 22% MM, and 43% CML, P < 0.001), reside in areas with higher socioeconomic disparity (40% vs. 26%, P < 0.001), and with Medicaid insurance (20% Medicare, 24% commercial, 59% Medicaid, and 14% multiple, P < 0.001).

Patients with AFEs had significantly delayed TTI (48 vs. 41 days, bivariate P = 0.01, multivariate P = 0.02). Similarly, patients with AFEs were more likely to have prolonged treatment start of TTI greater than 60 days (21% vs. 14%, bivariate P = 0.01, multivariate OR 1.66 [95% CI: 1.14-2.43], P = 0.01). Age, sex, race, disease type, geographic socioeconomic disparity, and insurance type were not significantly associated with TTI in both multivariable analyses.

Discussion Insured patients with hematologic malignancies with AFEs had delayed TTI, suggesting that financial hardship at diagnosis may be a barrier to high-quality care, even among patients with health insurance. Nearly a quarter of all patients – not limited to and more than double of Medicaid enrollees – had significant financial hardship at diagnosis. This suggests patients with AFEs may benefit from targeted financial navigation at diagnosis. We are leveraging patient data at FHCC to evaluate the impact of AFEs on treatment response and overall survival to evaluate the clinical impact of financial hardship, with the aim to inform intervention design to address financial disparities and ensure equitable care.

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2025
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