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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Multiplex Serum Protein Analysis Identifies Novel Biomarkers of Advanced Fibrosis in Patients with Chronic Liver Disease with the Potential to Improve Diagnostic Accuracy of Established Biomarkers
|
|---|---|
| Published in |
PLOS ONE, November 2016
|
| DOI | 10.1371/journal.pone.0167001 |
| Pubmed ID | |
| Authors |
Katharine M. Irvine, Leesa F. Wockner, Isabell Hoffmann, Leigh U. Horsfall, Kevin J. Fagan, Veonice Bijin, Bernett Lee, Andrew D. Clouston, Guy Lampe, John E. Connolly, Elizabeth E. Powell |
| Abstract |
Non-invasive markers of liver fibrosis are urgently required, especially for use in non-specialist settings. The aim of this study was to identify novel serum biomarkers of advanced fibrosis. We performed an unbiased screen of 120 serum analytes including cytokines, chemokines and proteases in 70 patients (35 without fibrosis, 35 with cirrhosis on biopsy), and selected a panel of 44 candidate biomarkers, which were subsequently measured in a mixed-etiology cohort of 432 patients with known serum HA, PIIINP and TIMP1 (which comprise the validated Enhanced Liver Fibrosis (ELF) test). Multivariate logistic regression modelling was used to generate models for the prediction of advanced or significant fibrosis (METAVIR ≥F3 and ≥F2, respectively); in addition to identifying biomarkers of disease activity and steatohepatitis. Seventeen analytes were significantly differentially expressed between patients with no advanced fibrosis and patients with advanced fibrosis, the most significant being hyaluronic acid (HA) and matrix metalloproteinase (MMP) 7 (p = 2.9E-41 and p = 1.0E-26, respectively). The optimal model for the prediction of advanced fibrosis comprised HA, MMP7, MMP1, alphafetoprotein (AFP) and the AST to platelet ratio index (APRI). We demonstrate enhanced diagnostic accuracy (AUROC = 0.938) compared to a model comprising HA, PIIINP and TIMP1 alone (ELF) (AUROC = 0.898, p<0.0001, De Long's test). We have identified novel serum biomarkers of advanced liver fibrosis, which have the potential to enhance the diagnostic accuracy of established biomarkers. Our data suggest MMP7 is a valuable indicator of advanced fibrosis and may play a role in liver fibrogenesis. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 3% |
| Unknown | 32 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 18% |
| Student > Master | 6 | 18% |
| Student > Ph. D. Student | 4 | 12% |
| Other | 4 | 12% |
| Student > Bachelor | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 8 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 21% |
| Biochemistry, Genetics and Molecular Biology | 5 | 15% |
| Agricultural and Biological Sciences | 2 | 6% |
| Engineering | 2 | 6% |
| Immunology and Microbiology | 2 | 6% |
| Other | 5 | 15% |
| Unknown | 10 | 30% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 07 November 2023.
All research outputs
#2,257,265
of 22,901,818 outputs
Outputs from PLOS ONE
#28,722
of 195,245 outputs
Outputs of similar age
#47,274
of 415,686 outputs
Outputs of similar age from PLOS ONE
#549
of 3,865 outputs
Altmetric has tracked 22,901,818 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 195,245 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.1. This one has done well, scoring higher than 85% 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 415,686 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 3,865 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.