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Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States

PURPOSE: Sufficient radiotherapy (RT) capacity is essential to delivery of high-quality cancer care. However, despite sufficient capacity, universal access is not always possible in high-income countries because of factors beyond the commonly used parameter of machines per million people. This study...

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Autores principales: Beckett, Matthew, Goethals, Luc, Kraus, Ryan D., Denysenko, Kseniya, Barone Mussalem Gentiles, Maria Fernanda, Pynda, Yaroslav, Abdel-Wahab, May
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581634/
https://www.ncbi.nlm.nih.gov/pubmed/37769217
http://dx.doi.org/10.1200/GO.23.00130
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author Beckett, Matthew
Goethals, Luc
Kraus, Ryan D.
Denysenko, Kseniya
Barone Mussalem Gentiles, Maria Fernanda
Pynda, Yaroslav
Abdel-Wahab, May
author_facet Beckett, Matthew
Goethals, Luc
Kraus, Ryan D.
Denysenko, Kseniya
Barone Mussalem Gentiles, Maria Fernanda
Pynda, Yaroslav
Abdel-Wahab, May
author_sort Beckett, Matthew
collection PubMed
description PURPOSE: Sufficient radiotherapy (RT) capacity is essential to delivery of high-quality cancer care. However, despite sufficient capacity, universal access is not always possible in high-income countries because of factors beyond the commonly used parameter of machines per million people. This study assesses the barriers to RT in a high-income country and how these affect cancer mortality. METHODS: This cross-sectional study used US county-level data obtained from Center for Disease Control and Prevention and the International Atomic Energy Agency Directory of Radiotherapy Centres. RT facilities in the United States were mapped using Geographic Information Systems software. Univariate analysis was used to identify whether distance to a RT center or various socioeconomic factors were predictive of all-cancer mortality-to-incidence ratio (MIR). Significant variables (P ≤ .05) on univariate analysis were included in a step-wise backward elimination method of multiple regression analysis. RESULTS: Thirty-one percent of US counties have at least one RT facility and 8.3% have five or more. The median linear distance from a county's centroid to the nearest RT center was 36 km, and the median county all-cancer MIR was 0.37. The amount of RT centers, linear accelerators, and brachytherapy units per 1 million people were associated with all-cancer MIR (P < .05). Greater distance to RT facilities, lower county population, lower average income per county, and higher proportion of patients without health insurance were associated with increased all-cancer MIR (R-squared, 0.2113; F, 94.22; P < .001). CONCLUSION: This analysis used unique high-quality data sets to identify significant barriers to RT access that correspond to higher cancer mortality at the county level. Geographic access, personal income, and insurance status all contribute to these concerning disparities. Efforts to address these barriers are needed.
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spelling pubmed-105816342023-10-18 Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States Beckett, Matthew Goethals, Luc Kraus, Ryan D. Denysenko, Kseniya Barone Mussalem Gentiles, Maria Fernanda Pynda, Yaroslav Abdel-Wahab, May JCO Glob Oncol ORIGINAL REPORTS PURPOSE: Sufficient radiotherapy (RT) capacity is essential to delivery of high-quality cancer care. However, despite sufficient capacity, universal access is not always possible in high-income countries because of factors beyond the commonly used parameter of machines per million people. This study assesses the barriers to RT in a high-income country and how these affect cancer mortality. METHODS: This cross-sectional study used US county-level data obtained from Center for Disease Control and Prevention and the International Atomic Energy Agency Directory of Radiotherapy Centres. RT facilities in the United States were mapped using Geographic Information Systems software. Univariate analysis was used to identify whether distance to a RT center or various socioeconomic factors were predictive of all-cancer mortality-to-incidence ratio (MIR). Significant variables (P ≤ .05) on univariate analysis were included in a step-wise backward elimination method of multiple regression analysis. RESULTS: Thirty-one percent of US counties have at least one RT facility and 8.3% have five or more. The median linear distance from a county's centroid to the nearest RT center was 36 km, and the median county all-cancer MIR was 0.37. The amount of RT centers, linear accelerators, and brachytherapy units per 1 million people were associated with all-cancer MIR (P < .05). Greater distance to RT facilities, lower county population, lower average income per county, and higher proportion of patients without health insurance were associated with increased all-cancer MIR (R-squared, 0.2113; F, 94.22; P < .001). CONCLUSION: This analysis used unique high-quality data sets to identify significant barriers to RT access that correspond to higher cancer mortality at the county level. Geographic access, personal income, and insurance status all contribute to these concerning disparities. Efforts to address these barriers are needed. Wolters Kluwer Health 2023-09-28 /pmc/articles/PMC10581634/ /pubmed/37769217 http://dx.doi.org/10.1200/GO.23.00130 Text en © 2023 by American Society of Clinical Oncology https://creativecommons.org/licenses/by/4.0/Licensed under the Creative Commons Attribution 4.0 License: http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/)
spellingShingle ORIGINAL REPORTS
Beckett, Matthew
Goethals, Luc
Kraus, Ryan D.
Denysenko, Kseniya
Barone Mussalem Gentiles, Maria Fernanda
Pynda, Yaroslav
Abdel-Wahab, May
Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States
title Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States
title_full Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States
title_fullStr Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States
title_full_unstemmed Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States
title_short Proximity to Radiotherapy Center, Population, Average Income, and Health Insurance Status as Predictors of Cancer Mortality at the County Level in the United States
title_sort proximity to radiotherapy center, population, average income, and health insurance status as predictors of cancer mortality at the county level in the united states
topic ORIGINAL REPORTS
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10581634/
https://www.ncbi.nlm.nih.gov/pubmed/37769217
http://dx.doi.org/10.1200/GO.23.00130
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