Geographic distribution of malignant mesothelioma incidence and survival in Australia

• Published in: Lung cancer (Amsterdam, Netherlands) Vol. 167; pp. 17 - 24
• Main Authors: Cameron, Jessica K., Aitken, Joanne, Reid, Alison, Mengersen, Kerrie, Cramb, Susanna, Preston, Paige, Armstrong, Bruce, Baade, Peter
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier B.V 01.05.2022
• Subjects: Asbestos; Australia - epidemiology; Bayes Theorem; Cancer; Humans; Incidence; Lung Neoplasms - epidemiology; Lung Neoplasms - etiology; Mesothelioma; Mesothelioma, Malignant; Occupational Exposure; Spatial modeling; Statistical modeling; Survival; Australia; Statistical modeling; MEET; CI; MESOTHELIOMA; SIR; Survival; EHR; Cancer; Incidence; Spatial modeling; Mesothelioma
• ISSN: 0169-5002; 1872-8332
• DOI: 10.1016/j.lungcan.2022.03.017

•There was strong evidence of spatial variation in incidence rates for mesothelioma in Australia.•Maps of modelled incidence counts show areas of greatest demand for health services.•Modelled incidence rates were higher in major cities and lower in affluent areas.•Some patterns were consistent with historical exposures, despite long latency. To understand the geographic distribution of and area-level factors associated with malignant mesothelioma incidence and survival in Australia. Generalised linear models and Bayesian spatial models were fitted using population registry data. Area-level covariates were socioeconomic quintile, remoteness category and state or territory. The maximised excess events test was used to test for spatial heterogeneity. There was strong evidence of spatial differences in standardised incidence rates for malignant mesothelioma but survival was uniformly poor. Incidence rates varied by state or territory and were lower in remote areas. Patterns in the geographic distribution of modelled incidence counts for malignant mesothelioma differed substantially from patterns of standardised incidence rates. Geographic variation in the modelled incidence counts of malignant mesothelioma demonstrates varying demand for diagnostic and management services. The long latency period for this cancer coupled with migration complicates any associations with patterns of exposure, however some of the geographic distribution of diagnoses can be explained by the location of historical mines and asbestos-related industries.