Geographical patterns in melanoma incidence across Australia: can thickness differentials reveal the key drivers?

, , , Soyer, H. Peter, , & (2020) Geographical patterns in melanoma incidence across Australia: can thickness differentials reveal the key drivers? Annals of Cancer Epidemiology, 4, Article number: 11.

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Description

Background: Australia has the highest rates of melanoma incidence in the world, but these vary across the country. It is unclear what drives the observed variation, but one potential cause could be differences in early detection. To investigate this, our study sought to determine the small-area melanoma patterns by thickness.

Methods: Bayesian hierarchical models were applied to all primary invasive melanoma cases diagnosed during 2010–2014 in Australian residents aged 15+ years to model rates across 2,148 small areas based on the Australian Statistical Geography Standard framework. A multivariate spatial model which included all 4 thickness categories [thin (≤1 mm), intermediate (>1–2 mm), thick (>2 mm) and missing] was used to examine geographic patterns by thickness and correlation between thicknesses.

Results: The majority (62%) of melanomas diagnosed were thin melanomas. The highest rates of melanoma diagnosis were across south-east Queensland and northern NSW, and these areas were consistently above the national average for each thickness category. In contrast, much of northern, central and western Australia tended to be below the national average diagnosis rate, and these geographical patterns were also largely consistent across all thickness categories.

Conclusions: The general consistency of geographical patterns of melanoma incidence across thickness categories suggests that the overall patterns are more likely to be due to the underlying population risk profile than differences in diagnostic practices.

Impact and interest:

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ID Code: 239026
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Cramb, Susanna M.orcid.org/0000-0001-9041-9531
Mengersen, Kerrie L.orcid.org/0000-0001-8625-9168
Baade, Peter D.orcid.org/0000-0001-8576-8868
Measurements or Duration: 12 pages
DOI: 10.21037/ace-20-13
ISSN: 2616-4213
Pure ID: 128860100
Divisions: Current > Research Centres > Centre for Data Science
Current > Research Centres > Centre for Healthcare Transformation
Current > Research Centres > Australian Centre for Health Services Innovation
Past > QUT Faculties & Divisions > Faculty of Health
Past > Institutes > Institute of Health and Biomedical Innovation
Past > QUT Faculties & Divisions > Science & Engineering Faculty
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Current > QUT Faculties and Divisions > Faculty of Science
Current > QUT Faculties and Divisions > Faculty of Health
Copyright Owner: Annals of Cancer Epidemiology
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Deposited On: 05 Apr 2023 23:51
Last Modified: 01 Mar 2024 01:39