Document Type
Article
Publication Date
9-2-2024
Original Citation
DiBiase J,
Scharnetzki E,
Edelman E,
Reed K,
Helbig P,
Rueter J,
Miesfeldt S,
Frankenfeld C,
Han P,
Jacobs E,
Anderson E,
.
Socioeconomic and urban-rural disparities in genome-matched treatment receipt and survival after genomic tumor testing. JNCI Cancer Spectr. 2024;8(5):pkae090
Keywords
MCGI, Humans, Male, Female, Middle Aged, Educational Status, Neoplasms, Rural Population, Aged, Proportional Hazards Models, Healthcare Disparities, Socioeconomic Factors, Kaplan-Meier Estimate, Maine, Urban Population, Income, Logistic Models, Adult, Genomics, Genetic Testing
JAX Source
JNCI Cancer Spectr. 2024;8(5):pkae090
ISSN
2515-5091
PMID
39312685
DOI
https://doi.org/10.1093/jncics/pkae090
Grant
This work was supported by funding from Harold Alfond Foundation; the Jackson Laboratory; and the National Center for Advancing Translational Sciences, National Institutes of Health (Grant Number KL2TR002545 to ECA). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Abstract
BACKGROUND: Emerging cancer treatments are often most available to socially advantaged individuals. This study examines the relationship of patient educational attainment, income level, and rurality to the receipt of genome-matched treatment and overall survival.
METHODS: Survey and clinical data were collected from patients with cancer (n = 1258) enrolled in the Maine Cancer Genomics Initiative. Logistic regression models examined whether receipt of genome-matched treatment differed by patient education, income, and rurality. Kaplan-Meier curves and Cox regression were conducted to evaluate 12-month mortality. We completed additional exploratory analyses using Kaplan-Meier curves and Cox models stratified by receipt of genome-matched treatment. Logistic and Cox regression models were adjusted for age and gender.
RESULTS: Educational attainment, income level, and rurality were not associated with genome-matched treatment receipt. Of 1258 patients, 462 (36.7%) died within 365 days of consent. Mortality risk was associated with lower educational attainment (hazard ratio [HR] = 1.30, 95% confidence interval [CI] = 1.06 to 1.59; P = .013). No statistically significant differences in mortality risk were observed for income level or rurality. Exploratory models suggest that patients who did not receive genome-matched treatment with lower educational attainment had higher mortality risk (HR = 1.36, 95% CI = 1.09 to 1.69; P = .006). For patients who did receive genome-matched treatment, there was no difference in mortality risk between the education groups (HR = 1.01, 95% CI = 0.56 to 1.81; P > .9).
CONCLUSION: Although there were no disparities in who received genome-matched treatment, we found a disparity in mortality associated with education level, which was more pronounced for patients who did not receive genome-matched treatment. Future research is warranted to investigate the intersectionality of social disadvantage with clinical outcomes to address survival disparities.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.