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A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment

Overview of attention for article published in Theoretical Biology and Medical Modelling, May 2014
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  • Above-average Attention Score compared to outputs of the same age and source (56th percentile)

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Citations

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Title
A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment
Published in
Theoretical Biology and Medical Modelling, May 2014
DOI 10.1186/1742-4682-11-24
Pubmed ID
Authors

Sibylle Schirm, Christoph Engel, Markus Loeffler, Markus Scholz

Abstract

Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Unknown 50 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 29%
Student > Ph. D. Student 5 10%
Other 3 6%
Student > Master 2 4%
Lecturer 1 2%
Other 4 8%
Unknown 21 41%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 6 12%
Agricultural and Biological Sciences 5 10%
Mathematics 4 8%
Medicine and Dentistry 4 8%
Biochemistry, Genetics and Molecular Biology 3 6%
Other 6 12%
Unknown 23 45%
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 26 May 2014.
All research outputs
#15,301,167
of 22,756,196 outputs
Outputs from Theoretical Biology and Medical Modelling
#170
of 287 outputs
Outputs of similar age
#132,442
of 226,319 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#6
of 16 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 226,319 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.