Evidence map›Paper›PMID 28382281›Full record

ReviewJournal of cancer prevention2017

Predictive and Prognostic Biomarkers of Respiratory Diseases due to Particulate Matter Exposure.

Hyo Jeong Kim, Min Gi Choi, Moo Kyun Park, Young Rok Seo

Open access · diamondAbstract readReview
In one paragraph

Review in Journal of cancer prevention, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
5.8field-weighted citation impact, top 3% of its field
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

37 citing papers in PubMed, 86 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Update in Association between Lung Cancer and Air Pollution.Tuberculosis and respiratory diseases · 2025
    Article
  5. A Combined Extract fromAntioxidants (Basel, Switzerland) · 2024
    Article
  6. Article
  7. Review
  8. Review
  9. Early Origins of Chronic Obstructive Pulmonary Disease: Prenatal and Early Life Risk Factors.International journal of environmental research and public health · 2023
    Review
  10. Article
  11. Article
  12. Recent Insights into Particulate Matter (PMInternational journal of environmental research and public health · 2022
    Review
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

4 authors at 2 institutions in 1 country.

Hyo Jeong KimInstitute of Environmental Medicine for Green Chemistry, Department of Life Science, Dongguk Bio-Med Campus, Dongguk University, Goyang, Korea.
Min Gi ChoiInstitute of Environmental Medicine for Green Chemistry, Department of Life Science, Dongguk Bio-Med Campus, Dongguk University, Goyang, Korea.
Moo Kyun ParkDepartment of Otorhinolaryngology-Head and Neck Surgery, Seoul National University College of Medicine, Seoul, Korea.
Young Rok SeoInstitute of Environmental Medicine for Green Chemistry, Department of Life Science, Dongguk Bio-Med Campus, Dongguk University, Goyang, Korea.
Dongguk University · KRSeoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Air pollution is getting severe and concerns about its toxicity effects on airway and lung disease are also increasing. Particulate matter (PM) is major component of air pollutant. It causes respiratory diseases, such as asthma, chronic obstructive pulmonary disease, lung cancer, and so on. PM particles enter the airway and lung by inhalation, causing damages to them. Especially, PM

Indexed as

BiomarkerEpigenetic changeInflammationOxidative stressParticulate matter

Identifiers

PMID28382281
PMCPMC5380184
OpenAlexW2604106374

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.