{"doi":"10.1093/jncics/pkae090","title":"Socioeconomic and urban-rural disparities in genome-matched treatment receipt and survival after genomic tumor testing","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.","journal":"JNCI Cancer Spectrum","year":2024,"id":474116,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.7899,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":770130,"name":"Elizabeth Scharnetzki","orcid":"0000-0002-5727-0189","position":1,"is_corresponding":false},{"id":770133,"name":"Emily Edelman","orcid":"0000-0002-5747-5715","position":2,"is_corresponding":false},{"id":1115285,"name":"Kate Reed","orcid":"0000-0003-3307-8093","position":3,"is_corresponding":false},{"id":1115002,"name":"Petra Helbig","orcid":null,"position":4,"is_corresponding":false},{"id":264369,"name":"Jens Rueter","orcid":"0000-0002-9021-025X","position":5,"is_corresponding":false},{"id":78660,"name":"Susan Miesfeldt","orcid":"0000-0001-8227-3165","position":6,"is_corresponding":false},{"id":1310330,"name":"Cara L. 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