Evidence map›Paper›PMID 42634457›Full record

ArticleZhongguo fei ai za zhi = Chinese journal of lung cancer2026

[Detection Status and Cost Analysis of Community Pulmonary Nodule Screening 
with Mobile LDCT Combined with AI].

Jianjie Wang, Jun Tao, Meilan Zhou, Xiaojun Wang, Gang Wu, Zhengbin Zhang, Zhouqin Lu, Qinghong Lin, Tiantian Wang, Haozhe Zhang and 2 more

Abstract readEnglish Abstract
In one paragraph

Article in Zhongguo fei ai za zhi = Chinese journal of lung cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Jianjie WangDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Jun TaoDepartment of Public Health, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Meilan ZhouQiaokou District Department of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Xiaojun WangDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Gang WuQiaokou District Department of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Zhengbin ZhangDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Zhouqin LuDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Qinghong LinDepartment of Public Health, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Tiantian WangDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Haozhe ZhangDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Zhiyi ZhengQiaokou District Department of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.
Yuehua LiDepartment of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan 430030, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLung cancer is the malignant tumor with the highest morbidity and mortality in China. Low-dose computed tomography (LDCT) is the core method for early lung cancer screening, but traditional fixed-institution screening has the problem of insufficient accessibility at the grassroots level. This study aims to evaluate the detection characteristics and influencing factors of pulmonary nodules by mobile LDCT combined with artificial intelligence (AI) in urban communities of Wuhan, and conduct a preliminary cost analysis from the health system perspective, so as to provide scientific basis for optimizing early screening strategies for pulmonary nodules at the primary care level.

methodsA community‑based observational study between August 2024 and May 2025 were conducted. A total of 3436 residents in Wuhan communities completed questionnaire surveys and mobile LDCT scans, with a recruitment response rate of 26.7%. Pulmonary nodules were classified according to the Lung CT Screening Reporting and Data System (Lung-RADS). Multivariate Logistic regression model was used to analyze the independent influencing factors of clinically significant nodules (Lung-RADS category ≥3). Sensitivity analysis was performed by stepwise backward full-variable model, and multicollinearity was tested by variance inflation factor (VIF). Meanwhile, a descriptive cost analysis was conducted in accordance with the CHEERS 2022 statement.

resultsThe median age of the screened population was 63 years, with 38.7% male and 67.3% aged ≥60 years. The overall detection rate of pulmonary nodules was 84.6%, with clinically significant nodules detected in 10.4% and high-risk nodules in 3.2%. Multivariate Logistic regression analysis showed that age 60-79 years (OR=2.771, 95%CI: 1.004-7.646, P=0.049), age ≥80 years (OR=6.224, 95%CI: 1.813-21.369, P=0.004), heavy smoking (OR=1.919, 95%CI: 1.352-2.724, P<0.001), secondhand smoke exposure (OR=1.762, 95%CI: 1.200-2.586, P=0.004), exposure to harmful chemicals (OR=2.972, 95%CI: 1.881-4.695, P<0.001), long-term kitchen oil fume exposure (OR=1.411, 95%CI: 1.102-1.807, P=0.006), and family history of lung cancer (OR=1.866, 95%CI: 1.173-2.967, P=0.008) were independent risk factors for clinically significant nodules. The total cost of the project was 666,580 CNY, with an average screening cost of 194 CNY per person. Under the whole population strategy, the costs for detecting one clinically significant nodule and one high-risk nodule were 1857 and 6060 CNY, respectively. Screening targeted at individuals aged ≥60 years could cover 87.3% of high-risk nodules, with the cost per high-risk nodule detected reduced to 4676 CNY.

conclusionsMobile LDCT combined with AI-assisted screening can effectively identify high-risk individuals of pulmonary nodules in community settings. The elderly and people with multiple exposure risks should be the priority population for screening. This study provides localized screening efficiency parameters and cost data of this model, which can provide practical basis for the optimization of primary pulmonary nodule early screening strategies and subsequent complete health economic evaluation.

Indexed as

Artificial IntelligenceCosts and Cost AnalysisEarly Detection of CancerLung NeoplasmsTomography, X-Ray ComputedAgedFemaleHumansMaleMiddle AgedCommunity screeningCost‑effectiveness analysisLung neoplasmsMobile CTRisk factors

Identifiers

PMID42634457
PMCPMC13482740

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.