2024 World Conference on Lung Cancer (WCLC) - Posters-P4.17D.01 Incidence Correlation Between Different Diseases and Lung Cancer: A Global Cross-Sectional and Time-series Study

P4.17D.01 Incidence Correlation Between Different Diseases and Lung Cancer: A Global Cross-Sectional and Time-series Study

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The study "Incidence Correlation between Different Diseases and Lung Cancer: A Global Cross-sectional and Time-series Study" explores the relationship between various diseases and lung cancer using data from the Global Burden of Disease (GBD) database. Conducted by researchers from the First Affiliated Hospital of Guangzhou Medical University, the study analyzes data from 204 countries, focusing on the incidence of 102 diseases, accounting for factors such as the Socio-Demographic Index (SDI) and smoking rates between 1990 and 2019.<br /><br />The research identifies potential positive correlations between lung cancer and 40 diseases. Notable correlations include non-rheumatic valvular heart disease, peripheral artery disease, alopecia areata, schizophrenia, and vascular intestinal disorders, all showing significant positive associations with lung cancer. In addition, chronic diseases like chronic obstructive pulmonary disease (COPD), type 1 diabetes, Parkinson's disease, and psoriasis also exhibit positive correlations with lung cancer. Gender-specific findings are highlighted, such as positive correlations of gout with lung cancer in males and conditions like paralytic ileus, hernia, and rheumatoid arthritis in females.<br /><br />To understand the time lag effects of these correlations, the study employs a distributed lag non-linear model (DLNM). For instance, COPD shows a notable effect on lung cancer risk with varying time lags depending on incidence rates.<br /><br />The study's findings provide a comprehensive correlation map, contributing to the understanding of potential risk factors and comorbidities associated with lung cancer. This research could pave the way for further exploration of mechanisms linking lung cancer and associated diseases, offering a framework for population-level screening of risk factors. The study acknowledges the GBD for providing open-access data critical to this research.

Asset Subtitle

Jianfu Li

Meta Tag

Speaker Jianfu Li

Topic Global Health, Health Services & Health Economics

Keywords

lung cancer

disease correlation

Global Burden of Disease

Socio-Demographic Index

smoking rates

chronic diseases

distributed lag non-linear model

risk factors

comorbidities

population-level screening