Evidence map›Paper›PMID 30231375›Full record

ReviewAmerican Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting2018

Personalized Management of Advanced Kidney Cancer.

Jeffrey Graham, Daniel Y C Heng, James Brugarolas, Ulka Vaishampayan

Abstract readReview
In one paragraph

Review in American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 2 pooled it
3.7field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 2 syntheses or guidelines pooled it, 36 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. DNA Methylation inCancers · 2021
    Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. 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 at 1 institution in 1 country.

Jeffrey GrahamFrom the Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta, Canada; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX; Karmanos Cancer Institute, Wayne State University, Detroit, MI.
Daniel Y C HengFrom the Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta, Canada; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX; Karmanos Cancer Institute, Wayne State University, Detroit, MI.
James BrugarolasFrom the Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta, Canada; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX; Karmanos Cancer Institute, Wayne State University, Detroit, MI.
Ulka VaishampayanFrom the Tom Baker Cancer Centre, University of Calgary, Calgary, Alberta, Canada; Kidney Cancer Program, Simmons Comprehensive Cancer Center, University of Texas Southwestern Medical Center, Dallas, TX; Karmanos Cancer Institute, Wayne State University, Detroit, MI.
Ontario Institute for Cancer Research · CA

Funding

Tumor Biology and Microenvironment (Program 1)P30CA022453 · NCI · WAYNE STATE UNIVERSITY · PI PAUL M STEMMER · 1985 to 2026
$68.4M
NCI NIH HHS P30 CA022453
6 · The paper itself

Abstract

The treatment of renal cell carcinoma represents one of the great success stories in translational cancer research, with the development of novel therapies targeting key oncogenic pathways. These include drugs that target the VEGF and mTOR pathways, as well as novel immuno-oncology agents. Despite the therapeutic advancements, there is a paucity of well-validated prognostic and predictive biomarkers in advanced kidney cancer. With a number of highly effective therapies available across multiple lines, it will become increasingly important to develop a more tailored approach to treatment selection. Prognostic clinical models, such the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model, are routinely used for prognostication in clinical practice. The IMDC model has demonstrated a predictive capability in the context of these treatments including immune checkpoint inhibition. A number of promising molecular markers and gene expression signatures are being explored as prognostic and predictive biomarkers, but none are ready to be widely used for treatment selection. In this review, we will explore the current landscape of personalized care in metastatic renal cell carcinoma. This will include a focus on both prognostic and predictive factors as well as clinical applications of biology in kidney cancer.

Indexed as

Precision MedicineCarcinoma, Renal CellCombined Modality TherapyDisease ManagementHumansKidney NeoplasmsNeoplasm MetastasisNeoplasm StagingPrognosisTreatment Outcome

Identifiers

PMID30231375
PMCPMC6865066
OpenAlexW2804649716

What OpenQuestion holds

Textmetadata
LicenceTDM
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.