Evidence map›Paper›PMID 40375086›Full record

ArticleBMC public health2025

Cost-effectiveness of low-dose CT screening for non-smokers with a first-degree relative history of lung cancer.

Yin Liu, Xiaoli Guo, Huifang Xu, Xiaoyang Wang, Hongwei Liu, Hong Wang, Ruihua Kang, Qiong Chen, Ranran Qie, Mengfei Zhao and 5 more

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Yin LiuDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Xiaoli GuoDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Huifang XuDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Xiaoyang WangDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Hongwei LiuDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Hong WangDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Ruihua KangDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Qiong ChenDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Ranran QieDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Mengfei ZhaoDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Cheng ChengDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Liyang ZhengDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Shuzheng LiuDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China.
Youlin QiaoDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China. qiaoy@cicams.ac.cn.
Shaokai ZhangDepartment of Cancer Epidemiology, The Affiliated Cancer Hospital of Zhengzhou University & Henan Cancer Hospital, Zhengzhou, 450008, China. shaokaizhang@126.com.

Funding

Henan Province Key Research and Development project 221111310200Henan Province Medical Science and Technology Public Relations Plan Province Department joint construction project SBGJ202403020Henan Provincial Science and Technology Research Project 242102311158
6 · The paper itself

Abstract

backgroundLung cancer is the leading cause of cancer-related deaths worldwide, with non-smokers in China accounting for over 40% of cases. Despite the proven efficacy of low-dose computed tomography (LDCT) in early detection and reduction of lung cancer mortality, the current paradigm of lung cancer screening, heavily focused on smoking status and age, may inadequately address the unique risk factors associated with non-smokers, particularly those with a family history of the disease. This study evaluates the cost-effectiveness of LDCT screening for non-smokers with a first-degree relative (FDR) history of lung cancer, a group at particularly high-risk.

methodsWe developed a state-transition Markov model to evaluate the incremental cost-effectiveness ratios (ICERs) of 16 screening strategies for a hypothetical cohort of 100,000 non-smoking individuals aged 50 with a FDR history of lung cancer, considering various starting ages (50, 55, 60, 65 years) and intervals (one-off, annual, biennial, triennial). The willingness-to-pay (WTP) threshold was set at three times China's 2022 per-capita GDP. Sensitivity analyses, scenario analyses and subgroup analysis by sex, were conducted.

resultsCompared to no screening, all strategies except one-off screening at age 50, were cost-effective for both sexes. Biennial LDCT starting at age 55 was found to be most effective, with an ICER of CNY 68,932/QALY for males, and CNY 80,056/QALY for females. This cost-effectiveness probability for this strategy was approximately 90% for both sexes. Sensitivity analyses indicated that annual screening at age 55 was optimal without discounting. For males, biennial at age 60 was optimal if the FDR-related odds ratio for lung cancer incidence was below 1.492. Triennial screening at age 55 was optimal for females at full adherence. Ignoring disutility from false-positive results, annual at age 55 was optimal for both sexes.

conclusionsLDCT screening for non-smokers with a FDR history of lung cancer is cost-effective, especially biennial screening at 55. These findings support the development of more inclusive screening guidelines, which could enhance early detection and reduce mortality rates.

Indexed as

Early Detection of CancerLung NeoplasmsMass ScreeningNon-SmokersTomography, X-Ray ComputedAgedChinaCost-Benefit AnalysisFemaleHumansMaleMarkov ChainsMiddle AgedRadiation DosageCost-effectivenessLDCT screeningLung CancerModelling studyNon-smokers

Identifiers

PMID40375086
PMCPMC12079829

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LicenceCC BY-NC-ND
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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.