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A three-gene expression-based risk score can refine the European LeukemiaNet AML classification

Overview of attention for article published in Journal of Hematology & Oncology, September 2016
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Title
A three-gene expression-based risk score can refine the European LeukemiaNet AML classification
Published in
Journal of Hematology & Oncology, September 2016
DOI 10.1186/s13045-016-0308-8
Pubmed ID
Authors

Stefan Wilop, Wen-Chien Chou, Edgar Jost, Martina Crysandt, Jens Panse, Ming-Kai Chuang, Tim H. Brümmendorf, Wolfgang Wagner, Hwei-Fang Tien, Behzad Kharabi Masouleh

Abstract

Risk stratification based on cytogenetics of acute myeloid leukemia (AML) remains imprecise. The introduction of novel genetic and epigenetic markers has helped to close this gap and increased the specificity of risk stratification, although most studies have been conducted in specific AML subpopulations. In order to overcome this limitation, we used a genome-wide approach in multiple AML populations to develop a robust prediction model for AML survival. We conducted a genome-wide expression analysis of two data sets from AML patients enrolled into the AMLCG-1999 trial and from the Tumor Cancer Genome Atlas (TCGA) to develop a prognostic score to refine current risk classification and performed a validation on two data sets of the National Taiwan University Hospital (NTUH) and an independent AMLCG cohort. In our training set, using a stringent multi-step approach, we identified a small three-gene prognostic scoring system, named Tri-AML score (TriAS) which highly correlated with overall survival (OS). Multivariate analysis revealed TriAS to be an independent prognostic factor in all tested training and additional validation sets, even including age, current cytogenetic-based risk stratification, and three other recently developed expression-based scoring models for AML. The Tri-AML score allows robust and clinically practical risk stratification for the outcome of AML patients. TriAS substantially refined current ELN risk stratification assigning 44.5 % of the patients into a different risk category.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 20%
Other 3 10%
Student > Bachelor 3 10%
Professor 3 10%
Student > Postgraduate 3 10%
Other 6 20%
Unknown 6 20%
Readers by discipline Count As %
Medicine and Dentistry 8 27%
Agricultural and Biological Sciences 3 10%
Nursing and Health Professions 2 7%
Environmental Science 1 3%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 2 7%
Unknown 13 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 September 2016.
All research outputs
#20,340,423
of 22,886,568 outputs
Outputs from Journal of Hematology & Oncology
#1,035
of 1,192 outputs
Outputs of similar age
#294,422
of 337,395 outputs
Outputs of similar age from Journal of Hematology & Oncology
#26
of 31 outputs
Altmetric has tracked 22,886,568 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
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We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.