Evidence map›Paper›PMID 30621125›Full record

ReviewInternational journal of molecular sciences2019

Targeting Multiple Receptors to Increase Checkpoint Blockade Efficacy.

David J Zahavi, Louis M Weiner

Abstract readReview
In one paragraph

Review in International journal of molecular sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Can Soluble Immune Checkpoint Molecules on Exosomes Mediate Inflammation?Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2022
    Review
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
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  19. 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.

David J ZahaviDepartment of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University, Medical Center, 3800 Reservoir Rd NW, Washington, DC 20007, USA. djz8@georgetown.edu.
Louis M WeinerLombardi Comprehensive Cancer Center Chair, Department of Oncology, Georgetown University Medical Center, 3970 Reservoir Road NW Research Building E501, Washington, DC 20015, USA. weinerl@georgetown.edu.

Funding

National Institutes of Health CA511008, CA50633
6 · The paper itself

Abstract

Immune checkpoint blockade therapy is a powerful treatment strategy for many cancer types. Many patients will have limited responses to monotherapy targeted to a single immune checkpoint. Both inhibitory and stimulatory immune checkpoints continue to be discovered. Additionally, many receptors previously identified to play a role in tumor formation and progression are being found to have immunomodulatory components. The success of immunotherapy depends on maximizing pro-anti-tumor immunity while minimizing immunosuppressive signaling. Combining immune checkpoint targeted approaches with each other or with other receptor targets is a promising schema for future therapeutic regimen designs.

Indexed as

ImmunomodulationAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalB7-H1 AntigenCTLA-4 AntigenDrug Therapy, CombinationHumansIpilimumabNeoplasmsNivolumabProgrammed Cell Death 1 ReceptorTreatment OutcomeAntibodies, MonoclonalAntibodies, Monoclonal, HumanizedAntineoplastic Agents, ImmunologicalB7-H1 AntigenCTLA-4 AntigenIpilimumabNivolumabpembrolizumabProgrammed Cell Death 1 Receptortremelimumabcombination therapyimmune checkpointreceptor targets

Identifiers

PMID30621125
PMCPMC6337574

What OpenQuestion holds

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LicenceCC BY
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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.