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.

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.

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