Evidence map›Paper›PMID 31935901›Full record

ReviewCells2020

Monitoring Therapy Efficiency in Cancer through Extracellular Vesicles.

Ines Stevic, Gustav Buescher, Franz Lennard Ricklefs

Abstract readReview
In one paragraph

Review in Cells, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Extracellular vesicles in laboratory medicine: a review and outlook.Frontiers in cell and developmental biology · 2025
    Review
  6. Article
  7. Article
  8. Liquid Biopsy in the Clinical Management of Cancers.International journal of molecular sciences · 2024
    Review
  9. Review
  10. Review
  11. Article
  12. Review
  13. Mitochondrial-Derived Vesicles: The Good, the Bad, and the Ugly.International journal of molecular sciences · 2023
    Review
  14. Article
  15. Article
  16. Article
  17. Liquid biopsies in primary and secondary bone cancers.Cancer drug resistance (Alhambra, Calif.) · 2022
    Review
  18. Article
  19. Rapid Capture of Cancer Extracellular Vesicles by Lipid Patch Microarrays.Advanced materials (Deerfield Beach, Fla.) · 2021
    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.

Ines StevicDepartment of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.
Gustav BuescherI. Department of Medicine, University Medical Centre Hamburg-Eppendorf, 20251 Hamburg, Germany.
Franz Lennard RicklefsDepartment of Neurosurgery, University Medical Center Hamburg-Eppendorf, 20251 Hamburg, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs) are a heterogeneous group of membrane-enclosed vesicles made of a phospholipid bilayer and are secreted by all cell types. EVs are present in a variety of body fluids containing proteins, DNA, RNA species, and lipids, and play an important role in cell- to-cell communication and are worth being considered as biomarkers for both early diagnosis of cancer patients and real-time monitoring of treatment response. Recently, emerging evidence verified EVs to have crucial roles in cancer progression and metastasis and a great potential in therapeutic applications. In this review, we discuss the potential of EVs in monitoring the efficacy of cancer therapies.

Indexed as

Drug MonitoringAnimalsExtracellular VesiclesHumansImmune Checkpoint ProteinsNeoplasmsImmune Checkpoint Proteinschemoresistanceextracellular vesicles (EVs), cancertherapy monitoring

Identifiers

PMID31935901
PMCPMC7017260

What OpenQuestion holds

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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.