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Evaluation of the biomarker candidate MFAP4 for non-invasive assessment of hepatic fibrosis in hepatitis C patients

Overview of attention for article published in Journal of Translational Medicine, July 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)

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1 tweeter
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1 patent

Citations

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30 Mendeley
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Title
Evaluation of the biomarker candidate MFAP4 for non-invasive assessment of hepatic fibrosis in hepatitis C patients
Published in
Journal of Translational Medicine, July 2016
DOI 10.1186/s12967-016-0952-3
Pubmed ID
Authors

Thilo Bracht, Christian Mölleken, Maike Ahrens, Gereon Poschmann, Anders Schlosser, Martin Eisenacher, Kai Stühler, Helmut E. Meyer, Wolff H. Schmiegel, Uffe Holmskov, Grith L. Sorensen, Barbara Sitek

Abstract

The human microfibrillar-associated protein 4 (MFAP4) is located to extracellular matrix fibers and plays a role in disease-related tissue remodeling. Previously, we identified MFAP4 as a serum biomarker candidate for hepatic fibrosis and cirrhosis in hepatitis C patients. The aim of the present study was to elucidate the potential of MFAP4 as biomarker for hepatic fibrosis with a focus on the differentiation of no to moderate (F0-F2) and severe fibrosis stages and cirrhosis (F3 and F4, Desmet-Scheuer scoring system). MFAP4 levels were measured using an AlphaLISA immunoassay in a retrospective study including n = 542 hepatitis C patients. We applied a univariate logistic regression model based on MFAP4 serum levels and furthermore derived a multivariate model including also age and gender. Youden-optimal cutoffs for binary classification were determined for both models without restrictions and considering a lower limit of 80 % sensitivity (correct classification of F3 and F4), respectively. To assess the generalization error, leave-one-out cross validation (LOOCV) was performed. MFAP4 levels were shown to differ between no to moderate fibrosis stages F0-F2 and severe stages (F3 and F4) with high statistical significance (t test on log scale, p value <2.2·10(-16)). In the LOOCV, the univariate classification resulted in 85.8 % sensitivity and 54.9 % specificity while the multivariate model yielded 81.3 % sensitivity and 61.5 % specificity (restricted approaches). We confirmed the applicability of MFAP4 as a novel serum biomarker for assessment of hepatic fibrosis and identification of high-risk patients with severe fibrosis stages in hepatitis C. The combination of MFAP4 with existing tests might lead to a more accurate non-invasive diagnosis of hepatic fibrosis and allow a cost-effective disease management in the era of new direct acting antivirals.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

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 7 23%
Student > Ph. D. Student 7 23%
Other 2 7%
Student > Bachelor 2 7%
Researcher 2 7%
Other 4 13%
Unknown 6 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 17%
Medicine and Dentistry 5 17%
Agricultural and Biological Sciences 3 10%
Chemical Engineering 1 3%
Computer Science 1 3%
Other 6 20%
Unknown 9 30%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 20 October 2022.
All research outputs
#7,112,480
of 22,509,254 outputs
Outputs from Journal of Translational Medicine
#1,121
of 3,923 outputs
Outputs of similar age
#94,756
of 277,201 outputs
Outputs of similar age from Journal of Translational Medicine
#1
of 1 outputs
Altmetric has tracked 22,509,254 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 3,923 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has gotten more attention than average, scoring higher than 69% 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 277,201 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them