Evidence map›Paper›PMID 39661098›Full record

ArticleEuropean journal of epidemiology2024

Dyslipidemia progression and increased lung cancer risk: a prospective cohort study.

Yelin Shao, Wenyuan Li, Chi Pang Wen, Min Yang, Xian Ning, Kejia Hu, Xifeng Wu

Abstract read
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In one paragraph

Article in European journal of epidemiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Article
  2. [European journal of nuclear medicine and molecular imaging · 2026
    Article
  3. Article
  4. Article
  5. 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

7 authors.

Yelin Shao *Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058, China.
Wenyuan Li *Center of Clinical Big Data and Analytics of the Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058, China.
Chi Pang WenInstitute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan.
Min YangCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058, China.
Xian NingCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058, China.
Kejia HuCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058, China.
Xifeng WuCenter of Clinical Big Data and Analytics of the Second Affiliated Hospital, School of Public Health, Zhejiang University School of Medicine, 866 Yuhangtang Road, Hangzhou, Zhejiang, 310058, China. xifengw@zju.edu.cn.ORCID http://orcid.org/0000-0003-2980-8129

Funding

Healthy Zhejiang One Million People Cohort K20230085Key Research and Development Program of Zhejiang Province 2020C03002Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang 2019R01007Zhejiang Key Laboratory of Intelligent Preventive Medicine Zhejiang Key Laboratory of Intelligent Preventive Medicine
6 · The paper itself

Abstract

objectivesTo investigate the associations of changes in lipidemic profile with the risk of lung cancer incidence, and to elucidate how modifiable risk factors contribute to the associations. DESIGN AND

participantsThe prospective study enrolled a cohort of 137,075 individuals with lipidemic profiles spanning from January 1, 1996 to December 31, 2006 in the Taiwan MJ Cohort. Follow-up was extended from the second clinical visit until December 31, 2007, with an average duration of 6.3 years. Participants was divided into four groups based on alterations in their lipidemic profile within a 1-3 year interval subsequent to initial enrollment. The associations of changes in lipidemic profiles with the incidence of lung cancer were assessed with Cox proportional hazard models. Associations between modifiable risk factors and lipidemic profile changes were evaluated using multivariable logistic regression models.

resultsOf 137,075 participants with lipidemic profile, progression to dyslipidemia within a 3-year period was associated with elevated risks of lung cancer incidence (hazard ratio [HR] = 1.46; 95% CI: 1.01, 2.10) in comparison to persistent normolipidemic. However, reversion to normolipidemic did not contribute to a decreased lung cancer incidence risk (HR = 1.10; 95% CI: 0.74, 1.63), in comparison to persistent dyslipidemia. Body mass index and smoking as risk factors, along with physical activity as a protective factor, were associated with changes in lipidemic profile.

conclusionsWithin this large-scale cohort, progression to dyslipidemia emerged as a risk factor for lung cancer incidence, highlighting the significance of lipid control. The modifiable risk factors associated with dyslipidemia progression encompassed body mass index, physical activity, and smoking status, suggesting potential interventions targets.

Indexed as

Disease ProgressionDyslipidemiasLung NeoplasmsProportional Hazards ModelsAdultAgedBody Mass IndexFemaleHumansIncidenceMaleMiddle AgedProspective StudiesRisk FactorsSmokingTaiwanDynamic changesLipidemic profileLung cancerModifiable risk factors

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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.