Evidence map›Paper›PMID 29383200›Full record

ReviewOncotarget2017

Next-generation metabolomics in lung cancer diagnosis, treatment and precision medicine: mini review.

Li Yu, Kefeng Li, Xiaoye Zhang

Abstract readReview
In one paragraph

Review in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
49citing papers in PubMed, 1 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

49 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Plant Metabolomics: The Future of Anticancer Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2024
    Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Review
  16. Skin Cancer Metabolic Profile Assessed by Different Analytical Platforms.International journal of molecular sciences · 2023
    Review
  17. Article
  18. Review
  19. Article
  20. Review
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

3 authors.

Li YuDepartment of Oncology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, China.
Kefeng LiSchool of Medicine, University of California San Diego, San Diego, CA, USA.
Xiaoye ZhangDepartment of Oncology, Shengjing Hospital, China Medical University, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lung cancer is the leading cause of cancer-related death. Next-generation metabolomics is becoming a powerful emerging technology for studying the systems biology and chemistry of health and disease. This mini review summarized the main platforms of next-generation metabolomics and its main applications in lung cancer including early diagnosis, pathogenesis, classifications and precision medicine. The period covers between 2009 and August, 2017. The major issues and future directions of metabolomics in lung cancer research and clinical applications were also discussed.

Indexed as

biomarkerlung cancernext-generation metabolomicspathogenesisprecision medicine

Identifiers

PMID29383200
PMCPMC5777812

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.