Evidence map›Paper›PMID 28096717›Full record

ReviewKorean journal of radiology

Immune-Checkpoint Inhibitors in the Era of Precision Medicine: What Radiologists Should Know.

Marta Braschi-Amirfarzan, Sree Harsha Tirumani, Frank Stephen Hodi, Mizuki Nishino

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Korean journal of radiology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

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

  1. Pooled it
  2. Review
  3. Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Article
  10. Review
  11. Article
  12. Review
  13. Review
  14. Review
  15. Review
  16. Review
  17. 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

4 authors.

Marta Braschi-AmirfarzanDepartment of Radiology, Brigham and Women's Hospital and Dana Farber Cancer Institute, Boston, MA 02215, USA.
Sree Harsha TirumaniDepartment of Radiology, Brigham and Women's Hospital and Dana Farber Cancer Institute, Boston, MA 02215, USA.
Frank Stephen HodiDepartment of Medical Oncology and Medicine, Dana Farber Cancer Institue, Boston, MA 02215, USA.
Mizuki NishinoDepartment of Radiology, Brigham and Women's Hospital and Dana Farber Cancer Institute, Boston, MA 02215, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the past five years immune-checkpoint inhibitors have dramatically changed the therapeutic landscape of advanced solid and hematologic malignancies. The currently approved immune-checkpoint inhibitors include antibodies to cytotoxic T-lymphocyte antigen-4, programmed cell death (PD-1), and programmed cell death ligand (PD-L1 and PD-L2). Response to immune-checkpoint inhibitors is evaluated on imaging using the immune-related response criteria. Activation of immune system results in a unique toxicity profile termed immune-related adverse events. This article will review the molecular mechanism, clinical applications, imaging of immune-related response patterns and adverse events associated with immune-checkpoint inhibitors.

Indexed as

Antibodies, MonoclonalAntineoplastic AgentsB7-H1 AntigenCTLA-4 AntigenHumansImmunotherapyNeoplasmsPrecision MedicineProgrammed Cell Death 1 ReceptorAntibodies, MonoclonalAntineoplastic AgentsB7-H1 AntigenCTLA-4 AntigenCTLA4 protein, humanProgrammed Cell Death 1 ReceptorImmune-checkpoint inhibitorImmune-related Response CriteriaResponseToxicity

Identifiers

PMID28096717
PMCPMC5240494

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.