2935 - Analysis of Breast Cancer Patients' Suggestions for Interventions to Alleviate Financial Toxicity
Presenter(s)
K. Ziegler1, V. Natarajan1, J. Feinberg2, and J. Klein3; 1Maimonides Medical Center, Brooklyn, NY, 2Maimonides Breast Center, Brooklyn, NY, 3Department of Radiation Oncology, State University of New York (SUNY) Downstate Medical Sciences University and Maimonides Medical Center, Brooklyn, NY
Purpose/Objective(s): Financial toxicity (FT) is the burden patients face from out-of-pocket costs related to medical care. FT is associated with quality of life (QoL) and may predict survival. Specific interventions that would help patients with their FT can be difficult to determine. We report preliminary results of a qualitative analysis of patient responses to a question about sources of FT and areas for potential intervention.
Materials/Methods: Single-arm, single-institution, longitudinal, prospective study of patients receiving curative-intent breast cancer treatment at an urban safety-net hospital. Patients completed Comprehensive Score for Financial Toxicity (COST) and EORTC QLQ-C30 (C30) questionnaires at baseline and after 6 months. FT was assessed via total COST, C30 Question 28 (Q28) and C30 Global Health Status / QoL scores (QoL). Lower COST score means worse FT.
At 6 months, patients were also asked: “What do you think would help you feel better about the costs of your treatment?”. Qualitative responses were grouped by via thematic analysis. Numerical variables were analyzed via Kruskal Wallis test; categorical variables were analyzed with ?2 or Fisher exact test.
Results: 76 patients were included. 43 (57%) had radiotherapy. 31 (41%) were non-English speakers. Average age was 57.6 years old (SD = 12). 29 (38%) had private and 47 (62%) had public insurance (Medicaid and/or Medicare). 32 (42%) reported household income = $40k/year, 30 (40%) made > $40k/year, and 14 (18%) unknown.
Qualitative responses were grouped into: Better insurance [N=13 (17%)], job-related issues [N=5 (7%)], more cost transparency [N=6 (8%)], and more financial assistance (FA) [N=12 (16%)]. 8 (11%) patients did not respond and 32 (42%) reported no FT. The FA group had the lowest COST score at 6 months (mean 17.5, IQR: 11.5-20); the cost transparency group had the highest (mean 33, IQR: 23-35).
These demographic variables had statistically significant differences in distribution of response groups: Insurance status (private vs public; p = 0.034), income band (not reported vs = $40k/year vs > $40k/year; p = 0.026), Q28 at both baseline and 6 months (1 ‘not at all’ vs 2-4; p = 0.02), and COST at baseline and 6 months (p < 0.02 for both). Patients with public insurance and household income = $40k/year were more likely to report not experiencing FT.
No significant differences in the distribution based on primary language spoken (p = 0.075), age (p = 0.331), or QoL scores at baseline and 6 months (p > 0.1 for both).
Conclusion: Insurance issues, poor cost transparency, lack of financial assistance, and job-related issues contribute to FT. Patients with public insurance and lower income were less likely to report experiencing FT (possibly due to higher rates of public insurance). Further study with a larger cohort will validate these findings, but this study suggests themes to alleviating FT of cancer patients.