Evidence map›Paper›PMID 28382036›Full record

ReviewFrontiers in immunology2017

Tommaso Torcellan, Jessica Stolp, Tatyana Chtanova

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Frontiers in immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

17 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Immune Checkpoint Therapy: Tumor Draining Lymph Nodes in the Spotlights.International journal of molecular sciences · 2021
    Review
  5. Review
  6. Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Review
  14. The extracellular matrix in tumor progression and metastasis.Clinical & experimental metastasis · 2019
    Review
  15. Transgenic Mouse Models in Cancer Research.Frontiers in oncology · 2018
    Review
  16. Cancer Immunotherapy Getting Brainy: Visualizing the Distinctive CNS Metastatic Niche to Illuminate Therapeutic Resistance.Drug resistance updates : reviews and commentaries in antimicrobial and anticancer chemotherapy · 2017
    Review
  17. 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 at 1 institution in 1 country.

Tommaso TorcellanImmunology Division, Garvan Institute of Medical Research, Sydney, NSW, Australia; Faculty of Medicine, St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia.
Jessica StolpImmunology Division, Garvan Institute of Medical Research, Sydney, NSW, Australia; Faculty of Medicine, St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia.
Tatyana ChtanovaImmunology Division, Garvan Institute of Medical Research, Sydney, NSW, Australia; Faculty of Medicine, St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia.
Garvan Institute of Medical Research · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is ample evidence for both beneficial and harmful involvement of the immune system in tumor development and spread. Immune cell recruitment to tumors is essential not only for the success of anticancer immune therapies but also for tumor-induced immune suppression. Now that immune-based therapies are playing an increasingly important role in treatment of solid tumors such as metastatic melanomas, precise analysis of the

Indexed as

antitumor immune responsecellular dynamicsimmune suppressionintravital microscopyin vivo imagingmigration

Identifiers

PMID28382036
PMCPMC5360706
OpenAlexW2599219073

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.