LDCT uptake and determinants of lung cancer screening in Asia: a systematic review and meta-analysis

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Authors: Yue Hu, Yuntong Zhao, Pei Dong, Qiu Wq, Mao Ay
Cited by: 1
References: 65

Abstract

Importance: Low-dose computed tomography (LDCT) lung cancer screening (LCS) has been shown to significantly reduce mortality rates. As its effectiveness relies on LDCT uptake, understanding uptake rates and their determinants can enhance the implementation and effectiveness of screening programs. Objective: This study aimed to analyze LDCT uptake and its influencing factors in lung cancer screening within an Asian population. Methods: Studies published between 1 January 2011 and 31 October 2025 were retrieved from four databases, and those reporting LDCT uptake and/or the factors influencing it were included. A random-effects model was applied to combine the effect estimates and 95% confidence intervals. Subgroup analyses were conducted to explore heterogeneity. Results: < 0.05). Patient-level factors that facilitated participation included a family history of lung cancer (odds ratio [OR], 1.95; 95%CI, 1.45-2.63), harmful occupational exposure (OR, 1.48; 95%CI, 1.33-1.64), chronic respiratory diseases (OR, 1.97; 95%CI, 1.62-2.38), alcohol consumption (OR, 1.20; 95%CI, 1.06-1.36), passive smoking exposure (OR, 1.43; 95%CI, 1.24-1.64), a higher body mass index (BMI; OR, 1.12; 95%CI, 1.05-1.20), and higher education levels (OR, 1.35; 95%CI, 1.17-1.56). Patient-level barriers included being a man (OR, 0.61; 95%CI, 0.55-0.68), engaging in frequent exercise (OR, 0.89; 95%CI, 0.84-0.94), smoking (OR, 0.76; 95%CI, 0.66-0.88), and being middle-aged (OR, 0.92; 95%CI, 0.85-0.99). Conclusion: LDCT uptake for lung cancer screening is lower in Asia than in academic programs, and it varies widely due to program design and population characteristics. Adopting smaller-scale screening designs and targeting key populations may help improve implementation efforts. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42025641277, identifier CRD42025641277.

Fields of Study & Subjects

Lung Cancer Diagnosis and Treatment Radiomics and Machine Learning in Medical Imaging Radiology practices and education

Publication details

Journal / source
Frontiers in Public Health
Publisher
Frontiers Media SA
Volume
13
Pages
1751146–1751146
Publication date
2 February 2026
Language
EN