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Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study
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 mul...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9340538/ https://www.ncbi.nlm.nih.gov/pubmed/35923428 http://dx.doi.org/10.1016/j.eclinm.2022.101594 |
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author | Cao, Wei Tan, Fengwei Liu, Kuangyu Wu, Zheng Wang, Fei Yu, Yiwen Wen, Yan Qin, Chao Xu, Yongjie Zhao, Liang Tang, Wei Li, Jiang Dong, Xuesi Zheng, Yadi Yang, Zhuoyu Su, Kai Li, Fang Shi, Jufang Ren, Jiansong Liu, Yunyong Yu, Lianzheng Wei, Donghua Dong, Dong Cao, Ji Zhang, Shaokai Yan, Shipeng Wang, Ning Du, Lingbin Chen, Wanqing Li, Ni He, Jie |
author_facet | Cao, Wei Tan, Fengwei Liu, Kuangyu Wu, Zheng Wang, Fei Yu, Yiwen Wen, Yan Qin, Chao Xu, Yongjie Zhao, Liang Tang, Wei Li, Jiang Dong, Xuesi Zheng, Yadi Yang, Zhuoyu Su, Kai Li, Fang Shi, Jufang Ren, Jiansong Liu, Yunyong Yu, Lianzheng Wei, Donghua Dong, Dong Cao, Ji Zhang, Shaokai Yan, Shipeng Wang, Ning Du, Lingbin Chen, Wanqing Li, Ni He, Jie |
author_sort | Cao, Wei |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9340538 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-93405382022-08-02 Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study Cao, Wei Tan, Fengwei Liu, Kuangyu Wu, Zheng Wang, Fei Yu, Yiwen Wen, Yan Qin, Chao Xu, Yongjie Zhao, Liang Tang, Wei Li, Jiang Dong, Xuesi Zheng, Yadi Yang, Zhuoyu Su, Kai Li, Fang Shi, Jufang Ren, Jiansong Liu, Yunyong Yu, Lianzheng Wei, Donghua Dong, Dong Cao, Ji Zhang, Shaokai Yan, Shipeng Wang, Ning Du, Lingbin Chen, Wanqing Li, Ni He, Jie eClinicalMedicine Articles 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. Elsevier 2022-07-29 /pmc/articles/PMC9340538/ /pubmed/35923428 http://dx.doi.org/10.1016/j.eclinm.2022.101594 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Articles Cao, Wei Tan, Fengwei Liu, Kuangyu Wu, Zheng Wang, Fei Yu, Yiwen Wen, Yan Qin, Chao Xu, Yongjie Zhao, Liang Tang, Wei Li, Jiang Dong, Xuesi Zheng, Yadi Yang, Zhuoyu Su, Kai Li, Fang Shi, Jufang Ren, Jiansong Liu, Yunyong Yu, Lianzheng Wei, Donghua Dong, Dong Cao, Ji Zhang, Shaokai Yan, Shipeng Wang, Ning Du, Lingbin Chen, Wanqing Li, Ni He, Jie Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study |
title | Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study |
title_full | Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study |
title_fullStr | Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study |
title_full_unstemmed | Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study |
title_short | Uptake of lung cancer screening with low-dose computed tomography in China: A multi-centre population-based study |
title_sort | uptake of lung cancer screening with low-dose computed tomography in china: a multi-centre population-based study |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9340538/ https://www.ncbi.nlm.nih.gov/pubmed/35923428 http://dx.doi.org/10.1016/j.eclinm.2022.101594 |
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