Screening for Lung Cancer in Hong Kong

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Abstract Description

Lung cancer remains the leading cause of cancer incidence and mortality in Hong Kong. This is largely due to the fact that early-stage lung cancer is often asymptomatic, with over half of patients presenting with incurable metastatic disease. Randomized controlled trials have shown that lung cancer screening with low dose computed tomography leads to stage migration and reduces mortality among smokers, which is now recommended in many countries. However, in Hong Kong, lung cancer screening is not routinely implemented, primarily due to lack of local data and several ongoing challenges. Firstly, current recommendations, based on age and smoking history, may fail to identify up to half of at-risk smokers. In Hong Kong, up to 50% of lung cancer occur in non-smokers, meaning that many high-risk individuals fall outside existing screening criteria. Secondly, LDCT has a relatively low positive predictive value, resulting in frequent false positives, unnecessary invasive procedures, and overtreatment. Thirdly, access to screening is constrained by high costs and shortage of radiologists. Finally, public awareness, uptake and adherence to screening remain low, limiting the effectiveness of screening at the population level. 

Emerging technologies and strategies are showing promise in addressing these gaps. Advances in genomic and other risk factor profiling have enabled the development of integrated risk models that more accurately identify at-risk individuals than traditional criteria. Artificial intelligence is being incorporated into imaging workflows to improve nodule detection and malignancy risk assessment, while reducing dependence on radiologist interpretation and lowering costs. Non-invasive biomarkers, including plasma-based assays (e.g. methylomic, fragmentomics), breath and urine tests – offer additional value for refining eligibility and guiding the need for invasive workup. The Chinese University of Hong Kong is conducting a prospective study investigating the use of artificial intelligence as first-reader for lung cancer screening and nodule detection among high-risk never smokers. Interim results will be presented. With emerging data, we hope to establish an inclusive, precise and cost-effective lung cancer screening programme that benefit both smokers and non-smokers in Hong Kong.


Submission ID :
HAC1302
Submission Type
Clinical Assistant Professor
,
The Chinese University Of Hong Kong

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