Evidence map›Paper›PMID 26560727›Full record

Trial reportEuropean radiology2016

The radiogenomic risk score stratifies outcomes in a renal cell cancer phase 2 clinical trial.

Neema Jamshidi, Eric Jonasch, Matthew Zapala, Ronald L Korn, James D Brooks, Borje Ljungberg, Michael D Kuo

Abstract readClinical Trial, Phase IIRandomized Controlled Trial
PubMed Publisher
In one paragraph

Trial report in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
4.1field-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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. A radiogenomics biomarker based on tumor angiogenesis for non-invasive prognosis of clear cell renal cell carcinoma.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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  13. Clinical implications of intratumor heterogeneity: challenges and opportunities.Journal of molecular medicine (Berlin, Germany) · 2020
    Review
  14. Review
  15. Imaging Advances in the Management of Kidney Cancer.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2018
    Review
  16. Review
  17. Article
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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

7 authors at 5 institutions in 2 countries.

Neema JamshidiDepartment of Radiological Sciences, University of California-Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA.
Eric JonaschDepartment of Genitourinary Medical Oncology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
Matthew ZapalaDepartment of Radiological Sciences, University of California-Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA.
Ronald L KornScottsdale Medical Imaging, Scottsdale, AZ, USA.
James D BrooksDepartment of Urology, Stanford University School of Medicine, Stanford, CA, USA.
Borje LjungbergDepartment of Surgical and Perioperative Sciences, Urology and Andrology, Umea Hospital, Umea, Sweden.
Michael D KuoDepartment of Radiological Sciences, University of California-Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA. michaelkuo@mednet.ucla.edu.
University of California, Los Angeles · USStanford University · USThe University of Texas MD Anderson Cancer Center · USUmeå University · SEUniversity of California, San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo characterize a radiogenomic risk score (RRS), a previously defined biomarker, and to evaluate its potential for stratifying radiological progression-free survival (rPFS) in patients with metastatic renal cell carcinoma (mRCC) undergoing pre-surgical treatment with bevacizumab. METHODOLOGY: In this IRB-approved study, prospective imaging analysis of the RRS was performed on phase II clinical trial data of mRCC patients (n = 41) evaluating whether patient stratification according to the RRS resulted in groups more or less likely to have a rPFS to pre-surgical bevacizumab prior to cytoreductive nephrectomy. Survival times of RRS subgroups were analyzed using Kaplan-Meier survival analysis.

resultsThe RRS is enriched in diverse molecular processes including drug response, stress response, protein kinase regulation, and signal transduction pathways (P < 0.05). The RRS successfully stratified rPFS to bevacizumab based on pre-treatment computed tomography imaging with a median progression-free survival of 6 versus >25 months (P = 0.005) and overall survival of 25 versus >37 months in the high and low RRS groups (P = 0.03), respectively. Conventional prognostic predictors including the Motzer and Heng criteria were not predictive in this cohort (P > 0.05).

conclusionsThe RRS stratifies rPFS to bevacizumab in patients from a phase II clinical trial with mRCC undergoing cytoreductive nephrectomy and pre-surgical bevacizumab. KEY POINTS: • The RRS SOMA stratifies patient outcomes in a phase II clinical trial. • RRS stratifies subjects into prognostic groups in a discrete or continuous fashion. • RRS is biologically enriched in diverse processes including drug response programs.

Indexed as

NephrectomyAdultAgedAngiogenesis InhibitorsBevacizumabCarcinoma, Renal CellDisease-Free SurvivalFemaleHumansKaplan-Meier EstimateKidney NeoplasmsMaleMiddle AgedPrognosisProspective StudiesRisk AssessmentAngiogenesis InhibitorsBevacizumabBevacizumabImaging biomarkerImaging surrogateRadiogenomicsRenal cell carcinoma

Identifiers

PMID26560727
OpenAlexW2246224606

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.