false
Catalog
2023 World Conference on Lung Cancer (Posters)
P1.01. Lung Cancer Risk Prediction Model Incorpora ...
P1.01. Lung Cancer Risk Prediction Model Incorporating Liver Function Markers: a Prospective Cohort Study from the UK Biobank - PDF(Abstract)
Back to course
Pdf Summary
A study conducted using data from the UK Biobank found that there is a potential relationship between liver function markers and the risk of lung cancer. The study aimed to assess the predictive ability of these markers in lung cancer risk. The researchers used data from over 330,000 participants who provided blood samples between 2006 and 2010. They performed multivariate cox regression to analyze the relationship between liver function markers and lung cancer risk. The results showed that certain markers, such as albumin and alanine transaminase, were negatively correlated with lung cancer risk, while other markers, like alkaline phosphatase and gamma glutamyltransferase, were positively correlated. The researchers developed a lung cancer risk prediction model that incorporated these liver function markers. They found that this model had strong predictive ability, with improved area under the curve (AUC) and net reclassification improvement (NRI) compared to a model based solely on questionnaire variables. The model performed even better when applied to current and former smokers. In addition, the researchers found that the model had better discrimination than standard lung cancer screening criteria. In conclusion, the study suggests that circulating levels of liver function markers are associated with lung cancer risk, and that incorporating these markers into a risk prediction model can enhance its predictive ability.
Asset Subtitle
Xiang Yu Sun
Meta Tag
Speaker
Xiang Yu Sun
Topic
Risk Factors, Risk Reduction & Tobacco Control
Keywords
UK Biobank
liver function markers
lung cancer risk
predictive ability
blood samples
multivariate cox regression
albumin
alanine transaminase
alkaline phosphatase
×
Please select your language
1
English