2024 Latin America Conference on Lung Cancer (LALCA) - Posters-PP01.80: A World Map of Air Pollution and EGFR Prevalence

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The study investigates the association between air pollution, specifically fine particulate matter (PM2.5), and the prevalence of EGFR mutations in lung cancer patients globally. Fine particulate matter (PM2.5) is a significant environmental health issue, linked to 6.7 million premature deaths annually. Lung cancer in non-smokers ranks high among cancer-related deaths, and there's substantial evidence linking air pollution with lung cancer incidence and mortality.<br /><br />The study analyzed data from 69 countries, examining the correlation between average PM2.5 levels (from 2000 to 2020) and the prevalence of EGFR-mutant lung cancer, using linear regression models adjusted for the total number of non-small cell lung cancers (NSCLC). The global association was found to be moderately weak (R2 = 0.34), and further weakened when analyses were stratified by regions such as Europe, Asia, and Latin America (R2 = 0.15).<br /><br />Significant variation existed across nations; for example, China showed high PM2.5 levels and high EGFR-mutant prevalence, but this correlation was not typical globally. Discrepancies in findings could arise from differences in access to genetic profiling for lung cancer, potential biases in mutation prevalence due to over-selection or population sample differences, and exposure disparity within countries.<br /><br />The study suggests that understanding the relationship between PM2.5 and EGFR-mutant lung cancer is complex and influenced by various factors, such as genomic background and ancestry, potentially confounding direct associations. Hence, relying solely on PM2.5 levels to predict EGFR-mutant lung cancer prevalence may not be accurate without considering other contributory factors and variations in local testing practices.

Asset Subtitle

Luis Leonardo Rojas Puentes

Keywords

air pollution

PM2.5

EGFR mutations

lung cancer

non-smokers

global study

linear regression

genetic profiling

regional disparities

environmental health