Evidence map›Paper›PMID 28123304›Full record

ArticleOncoTargets and therapy2017

Lilin He, Yongxiang Shen

Open access · goldAbstract read
In one paragraph

Article in OncoTargets and therapy, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 4 pooled it
3.8field-weighted citation impact, top 7% 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

23 citing papers in PubMed, 4 syntheses or guidelines pooled it, 38 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Common Variants in One-Carbon Metabolism Genes (International journal of molecular sciences · 2023
    Article
  6. Review
  7. Article
  8. Lack of Association ofGenetics research · 2023
    Article
  9. Review
  10. Targeting purine metabolism in ovarian cancer.Journal of ovarian research · 2022
    Review
  11. Review
  12. Article
  13. Article
  14. Article
  15. Genes · 2021
    Review
  16. Review
  17. Article
  18. Article
  19. Review
  20. Investigating the methylation status ofMolecular biology research communications · 2019
    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

2 authors at 1 institution in 1 country.

Lilin HeDepartment of Oncology, The First People's Hospital of Tianmen City, Tianmen, Hubei Province, People's Republic of China.
Yongxiang ShenDepartment of Oncology, The First People's Hospital of Tianmen City, Tianmen, Hubei Province, People's Republic of China.
The First People's Hospital of Tianmen · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePrevious studies have found that many gene variations can be detected in both breast cancer and ovarian cancer, which is beneficial for the elaboration of the molecular origin of breast and ovarian cancer. Furthermore, many studies have explored the association of methylenetetrahydrofolate reductase ( MATERIALS AND

methodsA total of 50 studies with 19,260 cases and 26,364 controls including 39 studies for breast cancer and 8 studies for ovarian cancer were identified on searching through PubMed, Embase, Web of Science, China National Knowledge Infrastructure, WanFang, and Database of Chinese Scientific and Technical Periodicals (VIP). Allele model, dominant model, recessive model, homozygous model, and co-dominant model were applied to evaluate the association of

resultsA significantly increased breast cancer risk was observed in the overall analysis (for C vs T, OR =1.19, CI: 1.12-1.28,

conclusionThis meta-analysis demonstrates that

Indexed as

breast cancerC677Tmeta-analysisMTHFRovarian cancerpolymorphism

Identifiers

PMID28123304
PMCPMC5229257
OpenAlexW2570336062

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.