Evidence map›Paper›PMID 26870806›Full record

ArticleEBioMedicine2015

A Molecular Model for Predicting Overall Survival in Patients with Metastatic Clear Cell Renal Carcinoma: Results from CALGB 90206 (Alliance).

Hyung L Kim, Susan Halabi, Ping Li, Greg Mayhew, Jeff Simko, Andrew B Nixon, Eric J Small, Brian Rini, Michael J Morris, Mary-Ellen Taplin and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EBioMedicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

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

  1. Immunotherapy for metastatic renal cell carcinoma.The Cochrane database of systematic reviews · 2017
    Pooled it
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Hyung L KimCedars-Sinai Medical Center, Los Angeles, CA, United States.
Susan HalabiDepartment of Biostatistics and Bioinformatics, and Alliance Statistics and Data Center, Duke University, Durham, NC, United States.
Ping LiCedars-Sinai Medical Center, Los Angeles, CA, United States.
Greg MayhewGeneCentric Diagnostics, Durham, NC, United States.
Jeff SimkoUniversity of California at San Francisco, San Francisco, CA, United States.
Andrew B NixonGeneCentric Diagnostics, Durham, NC, United States.
Eric J SmallUniversity of California at San Francisco, San Francisco, CA, United States.
Brian RiniCleveland Clinic Taussig Cancer Institute, Cleveland, OH, United States.
Michael J MorrisMemorial Sloan Kettering Cancer Center, New York, NY, United States.
Mary-Ellen TaplinDana-Farber Cancer Institute, Boston, MA, United States.
Daniel GeorgeDepartment of Biostatistics and Bioinformatics, and Alliance Statistics and Data Center, Duke University, Durham, NC, United States.
Alliance for Clinical Trials in Oncology

Funding

Member Site CoreU10CA180821 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI Evanthia Galanis · 2014 to 2026
$177.3M
THE ALLIANCE NCTN BIOREPOSITORY AND BIOSPECIMEN RESOURCEU24CA196171 · NCI · WASHINGTON UNIVERSITY · PI Mine Cicek, Wendy Frankel · 2015 to 2026
$35.0M
Validation of prognostic and pathway signatures in lethal prostate cancerU01CA157703 · NCI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GLEAVE, MARTIN EDWIN, HALABI, SUSAN · 2011 to 2015
$2.5M
Expression profiling of renal cell carcinoma utilizing tissue from CALGB 90206R01CA133072 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI KIM, HYUNG L · 2008 to 2013
$2.3M
Prognostic Models of Clinical Outcomes In Men With Castration Resistant ProstateR01CA155296 · NCI · DUKE UNIVERSITY · PI HALABI, SUSAN · 2011 to 2014
$914k
NCI NIH HHS R01 CA133072NCI NIH HHS R01 CA155296NCI NIH HHS U01 CA157703NCI NIH HHS U10 CA180821NCI NIH HHS U24 CA196171
6 · The paper itself

Abstract

backgroundPrognosis associated with metastatic renal cell carcinoma (mRCC) can vary widely.

methodsThis study used pretreatment nephrectomy specimens from a randomized phase III trial. Expression levels of candidate genes were determined from archival tumors using the OpenArray® platform for TaqMan® RT-qPCR. The dataset was randomly divided at 2:1 ratio into training (n = 221) and testing (n = 103) sets to develop a multigene prognostic signature.

findingsGene expressions were measured in 324 patients. In the training set, multiple models testing 424 candidate genes identified a prognostic signature containing 8 genes plus MSKCC clinical risk factors. In the testing set, the time dependent (td) AUC for a prognostic model containing the 8 genes with and without MSKCC risk factors were 0.72 and 0.69, respectively. The tdAUC for the clinical risk factors alone was 0.61. Additional primary mRCCs from patients with mRCC (n = 12) were sampled in multiple sites and standard deviations of gene expressions within a tumor were used as a measure of heterogeneity. All 8 genes in the final prognostic model met our criteria for minimal heterogeneity.

conclusionsA molecular prognostic signature based on 8 genes was developed and is ready for external validation in this patient population and other related settings such as nonmetastatic RCC.

Indexed as

Models, MolecularAgedArea Under CurveBiomarkers, TumorCanadaCarcinoma, Renal CellFemaleGene Expression ProfilingHumansKaplan-Meier EstimateKidney NeoplasmsMaleMiddle AgedModels, StatisticalNeoplasm MetastasisPrognosisBiomarkers, TumorExpression profilePrognostic markersPrognostic signatureRenal cell carcinoma

Identifiers

PMID26870806
PMCPMC4740313

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.