Evidence map›Paper›PMID 37769217›Full record

ArticleJCO global oncology2023

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

Matthew Beckett, Luc Goethals, Ryan D Kraus, Kseniya Denysenko, Maria Fernanda Barone Mussalem Gentiles, Yaroslav Pynda, May Abdel-Wahab

Abstract read
In one paragraph

Article in JCO global oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

  1. Article
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  3. Geographic access to radiotherapy facilities in Japan.Journal of radiation research · 2026
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Matthew BeckettThe Ottawa Hospital Cancer Centre, Ottawa, Ontario, Canada.ORCID 0000-0002-4711-1002
Luc GoethalsInternational Atomic Energy Agency, Vienna, Austria.ORCID 0000-0001-5809-7966
Ryan D KrausInternational Atomic Energy Agency, Vienna, Austria.ORCID 0000-0002-5160-6358
Kseniya DenysenkoInternational Atomic Energy Agency, Vienna, Austria.ORCID 0009-0000-6848-5620
Maria Fernanda Barone Mussalem GentilesInternational Atomic Energy Agency, Vienna, Austria.
Yaroslav PyndaInternational Atomic Energy Agency, Vienna, Austria.ORCID 0009-0003-7213-4622
May Abdel-WahabInternational Atomic Energy Agency, Vienna, Austria.ORCID 0000-0002-5415-1387

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeSufficient 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.

methodsThis 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 (

resultsThirty-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 (

conclusionThis 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.

Indexed as

IncomeNeoplasmsCross-Sectional StudiesHumansInsurance, HealthSocioeconomic FactorsUnited States

Identifiers

PMID37769217
PMCPMC10581634

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.