Geospatial analyses demonstrate variation of cutaneous T-cell lymphomas across Australia, providing insights into possible causes.

in The British journal of dermatology by Belinda A Campbell, Peter D Baade, Paramita Dasgupta, Jessica K Cameron, Sandro V Porceddu, H Miles Prince, Karin Thursky

TLDR

  • The study investigates the geospatial patterns of Cutaneous T-cell lymphomas in Australia, finding significant disparities in diagnosis rates and a lack of correlation with solar UV exposure.
  • The findings have implications for achieving equity of care and improving access to cancer care for patients with CTCL, particularly in rural and socio-economically disadvantaged areas.

Abstract

Cutaneous T-cell lymphomas (CTCL) are rare with distinct diagnostic challenges. Equitable access to cancer care is a recognised priority, internationally. To date, the geospatial distribution of CTCL has not been definitively studied. Understanding the incidence and geographical distribution of patients with CTCL are critical first steps towards the ultimate goal of equity of care. Geospatial analyses also allow the opportunity to explore environmental causative factors: for CTCL, the contribution of ultraviolet (UV) radiation on causation remains unclear. We investigate geospatial patterns of CTCL incidence across Australia, compare to all rare cancers, and consider solar UV exposure on causality and diagnosis rates. All CTCL diagnoses (1/1/2000-31/12/2019) were obtained from the nation-wide dataset. Areas of residence were collected according to nationally-approved definitions. Bayesian spatial incidence models were applied. Geospatial distributions were visually analysed. The CTCL age-standardised incidence was 7.7 [95%CI:7.4-7.9] per million people in Australia. Diagnostic disparity was seen between Australian states/territories, with lower diagnosis rates in rural/remote and socio-economically disadvantaged areas. Incidence exceeded the national average within more densely populated capital cities. Visual comparisons of the geospatial distribution of CTCL revealed marked discordances with the geospatial patterns of all rare cancers and solar UV in Australia. Geographical heterogeneity in CTCL exists across Australia. Incidence reflects population density. Geospatial patterns of CTCL substantially differ from all rare cancers, with implications for the unique diagnostic challenges and unmet needs of this patient population. The distribution of CTCL across Australia does not support a causative link with UV exposure. Further global evaluation of geospatial patterns is warranted.

Overview

  • The study investigates the geospatial patterns of Cutaneous T-cell lymphomas (CTCL) across Australia, comparing it to all rare cancers and considering solar UV exposure on causality and diagnosis rates.
  • The study aims to understand the incidence and geographical distribution of patients with CTCL to achieve equity of care, considering the diagnostic challenges and unmet needs of this patient population.
  • The study uses a nationwide dataset of CTCL diagnoses from 1/1/2000 to 31/12/2019 and applies Bayesian spatial incidence models to analyze the geospatial distributions.

Comparative Analysis & Findings

  • The age-standardised incidence of CTCL in Australia is 7.7 per million people, with significant disparities in diagnosis rates between states/territories, particularly in rural/remote and socio-economically disadvantaged areas.
  • The incidence of CTCL in densely populated capital cities exceeded the national average, highlighting the importance of population density in CTCL incidence.
  • The geospatial patterns of CTCL substantially differ from all rare cancers in Australia, suggesting unique diagnostic challenges and unmet needs for this patient population.

Implications and Future Directions

  • The findings highlight the need for further evaluation of geospatial patterns of CTCL globally and its relation to environmental factors, such as UV exposure.
  • Future research should explore the underlying causes of the observed disparities in diagnosis rates and develop strategies to improve access to cancer care for these patients.
  • Studies should also investigate the relationship between CTCL incidence and population density to inform targeted interventions and health policy decisions.
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