Jessica F DiBiase, Elizabeth Scharnetzki, Emily Edelman, E Kate Reed, Petra Helbig, Jens Rueter, Susan Miesfeldt, Cara L Frankenfeld, Paul K J Han, Elizabeth A Jacobs, Eric C Anderson
{"title":"Socioeconomic and urban-rural disparities in genome-matched treatment receipt and survival after genomic tumor testing.","authors":"Jessica F DiBiase, Elizabeth Scharnetzki, Emily Edelman, E Kate Reed, Petra Helbig, Jens Rueter, Susan Miesfeldt, Cara L Frankenfeld, Paul K J Han, Elizabeth A Jacobs, Eric C Anderson","doi":"10.1093/jncics/pkae090","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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).</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":14681,"journal":{"name":"JNCI Cancer Spectrum","volume":" ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11483106/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JNCI Cancer Spectrum","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/jncics/pkae090","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
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.