Evidence map›Paper›PMID 39035210›Full record

ArticleJournal of the National Cancer Center2022

Cost-effectiveness of lung cancer screening by low-dose CT in China: a micro-simulation study.

Yihui Du, Yanju Li, Grigory Sidorenkov, Rozemarijn Vliegenthart, Marjolein A Heuvelmans, Monique D Dorrius, Harry J M Groen, Shiyuan Liu, Li Fan, Zhaoxiang Ye and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the National Cancer Center, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 3 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

4 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
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

12 authors.

Yihui DuDepartment of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Yanju LiDepartment of Radiology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Centre for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Grigory SidorenkovDepartment of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Rozemarijn VliegenthartDepartment of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Marjolein A HeuvelmansDepartment of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Monique D DorriusDepartment of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Harry J M GroenDepartment of Pulmonary Diseases, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Shiyuan LiuDepartment of Radiology, Shanghai Changzheng Hospital, the Second Military Medical University, Shanghai, China.
Li FanDepartment of Radiology, Shanghai Changzheng Hospital, the Second Military Medical University, Shanghai, China.
Zhaoxiang YeDepartment of Radiology, Tianjin's Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, National Clinical Research Centre for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Marcel J W GreuterDepartment of Radiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
Geertruida H de BockDepartment of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The effectiveness of lung cancer screening with low-dose computed tomography (LDCT) has been established. The current study evaluates the cost-effectiveness of lung cancer screening with LDCT in a general population in China. Methods: A previously validated micro-simulation model was used to simulate a cohort of men and women on a lifetime horizon in the presence and absence of LDCT screening. The modeling data were collected from numerous national and international sources. Simulated screening scenarios included different combinations of screening intervals and start and stop ages. Additional costs (valued in Chinese Yuan, CNY; 1 USD = 6.8976 CNY, 1 EUR = 7.8755 CNY in 2020), life-years gained (LYG) and mortality reduction due to screening were also determined. The costs and life-years were discounted by 3%. All results were scaled to 1,000 individuals. The average cost-effectiveness ratio (ACER) was calculated. A willingness-to-pay threshold of CNY 217.3k / LYG was considered. A healthcare system perspective was adopted. Results: Compared to no screening, lung cancer screening by LDCT in a general Chinese population yielded 21.0 - 36.7 LYG in men and 9.2 - 16.6 LYG in women across the scenarios. For men, biennial LDCT screening yielded an ACER of CNY 171.4k - 306.3k / LYG relative to no screening. Biennial screening performed between 55 and 75 years of age was optimal at the defined threshold; it resulted in CNY 174.6k / LYG and a lung cancer mortality reduction of 9.1%, and this scenario had a 75% probability of being cost-effective. For women, the ACER ranged from CNY 364.2k to 1193.3k / LYG. Conclusions: In China, lung cancer screening with LDCT in the general population including never smokers could be cost-effective for men with 75% probability, but not for women. The optimal strategy for men would be performing biennial screening between 55 and 75 years of age.

Indexed as

Cost-effectivenessGeneral populationLow-dose computed tomographyLung neoplasmMass screeningMicrosimulation model

Identifiers

PMID39035210
PMCPMC11256619

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Registered trials

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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.