Background: Optimal uptake rates of low-dose computed tomography (LDCT) scans are essential for lung cancer screening (LCS) to confer mortality benefits. We aimed to outline the process model of the LCS programme in China, identify the high-risk individuals with low uptake based on a prospective multi-centre population-based cohort, and further explore associated structural characteristics.
Methods: A total of 221,955 individuals at high-risk for lung cancer from the National Lung Cancer Screening cohort were included. The logistic regression model was performed to identify the individual characteristics associated with the uptake of LCS, defined as whether the high-risk individual undertook LDCT scans in designated hospitals within six months following the initial risk assessment. The linear regression model was adopted to explore the structural characteristics associated with the uptake rates in 186 communities.
Findings: The overall uptake rate was 33·0%. The uptake rate was negatively correlated with the incidence of advanced-stage lung cancer (Pearson's coefficient -0·88, p-value 0·0007). Multivariable regression models found that lower uptake rates were associated with males (OR 0·88, 95%CI 0·85-0·91), current smokers (OR 0·93, 95%CI 0·90-0·96), individuals with depressive symptoms (OR 0·92, 95%CI 0·90-0·94), and the structural characteristics, including longer structural delays in initiating LDCT scans (30-90 days vs. ≤14 days: β -7·17, 95%CI -12·76∼ -1·57; >90 days vs. ≤14 days: β -13·69, 95%CI -24·61∼ -2·76), no media-assisted publicity (β -6·43, 95%CI -11·26∼ -1·60), and no navigation assistance (β -5·48, 95%CI -10·52∼ -0·44).
Interpretation: Multifaceted interventions are recommended, which focus on poor-uptake individuals and integrate the 'assessment-to-timely-screening' approach to minimise structural delays, media publicity, and a navigation assistance along the centralised screening pathway.
Funding: Ministry of Finance and National Health Commission of the People's Republic of China.
Keywords: China; Lung cancer; Population-based study; Screening; Uptake.
© 2022 The Author(s).