# Examining the Association Between Equity-Related Factors and EQ-5D-3L Health Utilities of Patients with Cancer

## TL;DR

This study shows that cancer patients with lower incomes report worse quality of life, suggesting health assessments should consider socioeconomic factors.

## Contribution

The study is the first to demonstrate a significant link between low income and reduced health utilities in a real-world cancer patient sample.

## Key findings

- Lower EQ-5D-3L health utilities were significantly associated with the lowest and undisclosed income categories.
- Disutility estimates for lowest income and undisclosed income were statistically significant in regression models.
- Incorporating socioeconomic status in health utility assessments is critical for equitable health technology evaluation.

## Abstract

Background and existing knowledge: Health utilities are a measure of health-related quality of life (HRQoL) used in cancer drug funding decisions. These are often derived from clinical trials with highly selected, socioeconomically advantaged participants, which can over-estimate HRQoL. To address this issue, we explored associations between EQ-5D-3L health utilities across a range of socioeconomic statuses in a real-world sample of patients with cancer. New findings: We found that HRQoL measured through EQ-5D-3L health utilities was lowest in patients in the lowest (under CAD 29,000) and undisclosed income categories. Implications: Our findings suggest that HRQoL measured through EQ-5D-3L health utilities may be associated with socioeconomic status, particularly family income. These findings can be used to support equity-informed health technology assessment.

Background: EQ-5D-3L health utilities inform health technology assessments in oncology, often derived from clinical trials enrolling highly selected populations, which may over-estimate real-world health utilities. Little is known about the association between socioeconomic status (SES) and EQ-5D-3L health utilities. Our objective was to examine EQ-5D-3L health utilities across SES in a real-world sample of patients with cancer. Methods: We conducted a cross-sectional analysis of EQ-5D-3L responses from 170 adult patients with cancer accrued from an Ontario oncology centre. We fitted multivariable linear regression models to estimate associations between covariates and EQ-5D-3L health utilities. Results: Lower EQ-5D-3L health utilities were significantly associated with the lowest and undisclosed family income categories in models with and without birth sex (p < 0.05). In the model including birth sex, disutility estimates for lowest family income (<CAD 29K) and undisclosed income was −0.202, 95% CI (−0.371 to −0.033), and −0.123 (−0.235 to −0.012), respectively. For the model excluding birth sex, disutility estimates for lowest income and undisclosed income was −0.163 (−0.280 to −0.046) and −0.106 (−0.184 to −0.028). Conclusions: Lower EQ-5D-3L health utilities were significantly associated with low income and nondisclosure, highlighting the need to incorporate SES in analyzing health utilities in cancer care.