Evidence map›Paper›PMID 40520280›Full record

ArticleFrontiers in public health2025

Epidemiological association and machine learning-based prediction of lung cancer risk linked to long-term lagged satellite-derived PM

Feiran Wei, Shijun Yang, Huiying Wang, Meng Zhao, Jinyi Zhou, Xiaobing Shen, Renqiang Han, Gaoqiang Fei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Tumor Exposomics: A New Paradigm for Individualized Continuous Exposure Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  2. 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

8 authors.

Feiran WeiKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China.
Shijun YangGuangxi Meteorological Observatory, Nanjing, China.
Huiying WangLianyungang Meteorological Bureau, Lianyungang, China.
Meng ZhaoKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China.
Jinyi ZhouJiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing, China.
Xiaobing ShenKey Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing, China.
Renqiang HanJiangsu Provincial Center for Disease Control and Prevention (Jiangsu Provincial Academy of Preventive Medicine), Nanjing, China.
Gaoqiang FeiDepartment of Public Health, Jiangsu Cancer Hospital, The Affiliated Cancer Hospital of Nanjing Medical University, Jiangsu Institute of Cancer Research, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study investigated association between long-term PM Study design: An ecological epidemiology study. Methods: Lung cancer incidence data from Jiangsu Province (2014-2018) were combined with annual PM Results: The incidence of lung cancer was significantly correlated with PM Conclusion: Long-term exposure to PM

Indexed as

Air PollutantsAir PollutionEnvironmental ExposureLung NeoplasmsMachine LearningParticulate MatterChinaHumansIncidenceAir PollutantsParticulate Matterlong-term exposurelung cancermachine learningPM2.5prediction modelpublic health

Identifiers

PMID40520280
PMCPMC12162561

What OpenQuestion holds

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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.