Evidence map›Paper›PMID 28220024›Full record

ArticleThe oncologist2017

Molecular Subtypes Improve Prognostic Value of International Metastatic Renal Cell Carcinoma Database Consortium Prognostic Model.

Guillermo de Velasco, Aedín C Culhane, André P Fay, A Ari Hakimi, Martin H Voss, Nizar M Tannir, Pheroze Tamboli, Leonard J Appleman, Joaquim Bellmunt, W Kimryn Rathmell and 5 more

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in The oncologist, 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
8.0field-weighted citation impact, top 2% 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, 61 citations in OpenAlex.

  1. Trial
  2. Article
  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Observational
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Review
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors at 10 institutions in 5 countries.

Guillermo de VelascoDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Aedín C CulhaneDepartment of Biostatistics & Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
André P FayDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
A Ari HakimiDepartment of Surgery-Urology Service, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Martin H VossDepartment of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Nizar M TannirDepartment of Medical Oncology, MD Anderson Cancer Center, Houston, Texas, USA.
Pheroze TamboliDepartment of Pathology, MD Anderson Cancer Center, Houston, Texas, USA.
Leonard J ApplemanDivision of Hematology/Oncology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
Joaquim BellmuntDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
W Kimryn RathmellDivision of Hematology and Oncology, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Laurence AlbigesDepartment of Medical Oncology, Institut Gustave Roussy, Villejuif, France.
James J HsiehDepartment of Medical Oncology, Memorial Sloan Kettering Cancer Center, New York, New York, USA.
Daniel Y C HengDepartment of Medical Oncology, Tom Baker Cancer Center and University of Calgary, Calgary, Canada.
Sabina SignorettiDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
Toni K ChoueiriDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA Toni_Choueiri@dfci.harvard.edu.
Dana-Farber Cancer Institute · USMemorial Sloan Kettering Cancer Center · USThe University of Texas MD Anderson Cancer Center · USBrigham and Women's Hospital · USHarvard University · USInstitut Gustave Roussy · FRResearch Institute Hospital 12 de Octubre · ESUniversity of Calgary · CAUniversity of Pittsburgh · USVanderbilt University Medical Center · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
NCI NIH HHS P30 CA008748
6 · The paper itself

Abstract

introductionGene-expression signatures for prognosis have been reported in localized renal cell carcinoma (RCC). The aim of this study was to test the predictive power of two different signatures, ClearCode34, a 34-gene signature model [Eur Urol 2014;66:77-84], and an 8-gene signature model [Eur Urol 2015;67:17-20], in the setting of systemic therapy for metastatic disease. MATERIALS AND

methodsMetastatic RCC (mRCC) patients from five institutions who were part of TCGA were identified and clinical data were retrieved. We trained and implemented each gene model as described by the original study. The latter was demonstrated by faithful regeneration of a figure and results from the original study. mRCC patients were dichotomized to good or poor prognostic risk groups using each gene model. Cox proportional hazard regression and concordance index (C-Index) analysis were used to investigate an association between each prognostic risk model and overall survival (OS) from first-line therapy.

resultsOverall, 54 patients were included in the final analysis. The primary endpoint was OS. Applying the ClearCode34 model, median survival for the low-risk-ccA (

conclusionThe ClearCode34 but not the 8-gene molecular model improved the prognostic predictive power of the IMDC model in this cohort of 54 patients with metastatic clear cell RCC.

Indexed as

Molecular Targeted TherapyPrognosisAryl Hydrocarbon Receptor Nuclear TranslocatorBasic Helix-Loop-Helix ProteinsCarcinoma, Renal CellCohort StudiesDatabases, FactualDisease-Free SurvivalEndothelial PAS Domain-Containing Protein 1FemaleGene Expression Regulation, NeoplasticHumansMaleNeoplasms, Second PrimaryRisk FactorsARNT protein, humanAryl Hydrocarbon Receptor Nuclear TranslocatorBasic Helix-Loop-Helix ProteinsEndothelial PAS Domain-Containing Protein 1GenomicsmRCCPrognosisSignatureTCGA

Identifiers

PMID28220024
PMCPMC5344647
OpenAlexW2591210005

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.