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An 18 gene expression-based score classifier predicts the clinical outcome in stage 4 neuroblastoma

Overview of attention for article published in Journal of Translational Medicine, May 2016
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Title
An 18 gene expression-based score classifier predicts the clinical outcome in stage 4 neuroblastoma
Published in
Journal of Translational Medicine, May 2016
DOI 10.1186/s12967-016-0896-7
Pubmed ID
Authors

Daniela Formicola, Giuseppe Petrosino, Vito Alessandro Lasorsa, Piero Pignataro, Flora Cimmino, Simona Vetrella, Luca Longo, Gian Paolo Tonini, André Oberthuer, Achille Iolascon, Matthias Fischer, Mario Capasso

Abstract

The prognosis of children with metastatic stage 4 neuroblastoma (NB) has remained poor in the past decade. Using microarray analyses of 342 primary tumors, we here developed and validated an easy to use gene expression-based risk score including 18 genes, which can robustly predict the outcome of stage 4 patients. This classifier was a significant predictor of overall survival in two independent validation cohorts [cohort 1 (n = 214): P = 6.3 × 10(-5); cohort 2 (n = 27): P = 3.1 × 10(-2)]. The prognostic value of the risk score was validated by multivariate analysis including the established markers age and MYCN status (P = 0.027). In the pooled validation cohorts (n = 241), integration of the risk score with the age and/or MYCN status identified subgroups with significantly differing overall survival (ranging from 35 to 100 %). Together, the 18-gene risk score classifier can identify patients with stage 4 NB with favorable outcome and may therefore improve risk assessment and treatment stratification of NB patients with disseminated disease.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 1 4%
Unknown 27 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 25%
Student > Bachelor 3 11%
Student > Master 3 11%
Lecturer 2 7%
Student > Postgraduate 2 7%
Other 5 18%
Unknown 6 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 29%
Medicine and Dentistry 6 21%
Agricultural and Biological Sciences 3 11%
Unspecified 1 4%
Computer Science 1 4%
Other 1 4%
Unknown 8 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 June 2016.
All research outputs
#14,262,277
of 22,870,727 outputs
Outputs from Journal of Translational Medicine
#1,783
of 4,002 outputs
Outputs of similar age
#181,563
of 326,819 outputs
Outputs of similar age from Journal of Translational Medicine
#55
of 108 outputs
Altmetric has tracked 22,870,727 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,002 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 50% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,819 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.