Evidence map›Paper›PMID 28344662›Full record

ReviewTherapeutic advances in medical oncology2017

Nivolumab in renal cell carcinoma: latest evidence and clinical potential.

Camille Mazza, Bernard Escudier, Laurence Albiges

Open access · bronzeAbstract readReview
In one paragraph

Review in Therapeutic advances in medical oncology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
5.0field-weighted citation impact, top 3% 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

33 citing papers in PubMed, 66 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Renal Toxicity.Advances in experimental medicine and biology · 2021
    Review
  17. Article
  18. Article
  19. Review
  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 at 2 institutions in 1 country.

Camille MazzaDepartment of Medical Oncology, Gustave Roussy, Villejuif, France.
Bernard EscudierDépartement de médecine Oncologique, Gustave Roussy, Université Paris-Saclay, Villejuif, France.
Laurence AlbigesDépartement de médecine Oncologique, Gustave Roussy, Université Paris-Saclay, Villejuif, F-94805, 114 Rue Edouard Vaillant, 94800 Villejuif, France.
Institut Gustave Roussy · FRUniversité Paris-Saclay · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Similar to melanoma, renal cell carcinoma (RCC) has been historically considered as an immunogenic tumor, with interleukin 2 (IL-2) and interferon alpha (IFN-α) being the first approved treatments in the 1990s. However, these therapies were effective in only 10-20% of cases and were not well tolerated. Recently, new insights on the interaction between the immune system and tumor have identified the programmed death-1/programmed death-ligand-1 (PD-1/PD-L1) pathway to be a key player in evading host immune responses. The strategy of immune checkpoint blockade is to reduce inhibitory signaling and restore the patient's natural tumor-specific T-cell-mediated immune responses. Nivolumab is the first PD-1 inhibitor to have gained approval for the treatment of patients with metastatic melanoma, squamous and nonsquamous non-small cell lung cancer (NSCLC), Hodgkin disease and recently RCC. In this review, we discuss results from studies of nivolumab in RCC, clinical experience with this agent, and its future development.

Indexed as

immune checkpoint inhibitorimmunotherapynivolumabprogrammed death-1renal cell carcinoma

Identifiers

PMID28344662
PMCPMC5349425
OpenAlexW2563797543

What OpenQuestion holds

Textmetadata
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.