Journal article
CT scans in childhood predict subsequent brain cancer: Finite mixture modelling can help separate reverse causation scans from those that may be causal
NR Smoll, JD Mathews, KJ Scurrah
Cancer Epidemiology | ELSEVIER SCI LTD | Published : 2020
Abstract
Background: Excess brain cancers observed after computed tomography (CT) scans could be caused by ionizing radiation. However, as scans are often used to investigate symptoms of brain cancer, excess cancers could also be due to reverse causation bias. We used finite mixture models (FMM) to differentiate CT exposures that are plausibly causal from those due to reverse causation. Methods: Persons with at least one CT scan exposure and a subsequent diagnosis of brain cancer were selected from a cohort of 11 million young Australians. We fitted FMMs and used the posterior probability to inform the choice of exclusion periods. We validated our findings using a separate clinical dataset describing..
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Grants
Awarded by National Health and Medical Research Council
Funding Acknowledgements
This work was funded by the Australian Government through NHMRC grants 509190, 1027368, and 1084197.