ArticleClinical epidemiology2018
Number of radiotherapy treatment machines in the population and cancer mortality: an ecological study.
Article in Clinical epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Changes in essential cancer medicines and association with cancer outcomes: an observational study of 158 countries.BMC cancer · 2024Observational
- Essential cancer medicines and cancer outcomes: Cross-sectional study of 124 countries.Cancer medicine · 2023Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesThe aim of this study was to assess the association between the number of radiotherapy treatment machines (RTMs) in the population and incidence-adjusted cancer mortality.
methodsData on cancer incidence and mortality were obtained from the GLOBOCAN project (only high-quality data, C3, or higher according to GLOBOCAN quality label), information on the number of RTMs from the Directory of Radiotherapy Centers database, and remaining data from the World Bank and World Health Organization database. We used linear regression models to assess the associations between RTM per 10,000,000 inhabitants (logarithmized) and the log-transformed mortality/incidence ratio. Models were adjusted for public health variables. To assess the bias due to unobserved confounders, mortality from leukemia was considered as a negative control. Here radiotherapy treatment is less frequently applied, but a common set of confounders is shared with cancer types where radiotherapy plays a stronger role, enabling us to estimate the bias due to confounding of unmeasured parameters. To assess an exposure-effect size relationship, estimated cancer type-specific estimates were related to the proportion of subjects receiving radiotherapy.
resultsWe found an inverse linear relationship between RTM in the population and the cancer mortality to incidence ratio for prostate cancer (14.1% per doubling of RTM; 95% CI: 0.1%-26.1%), female breast cancer (12.3%; 95% CI: 2.7%-20.9%), and lung cancer in women (11.2%; 95% CI: 4.3%-17.6%). There was no evidence for bias due to unobserved confounders after covariate adjustment. For women, an exposure-effect size relationship was found (
conclusionIn this ecological study, we found evidence that the population density of RTM is related to cancer mortality independently of other public health parameters.
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