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Prognostic biomarkers to identify patients destined to develop severe Crohn’s disease who may benefit from early biological therapy: protocol for a systematic review, meta-analysis and external…

Overview of attention for article published in Systematic Reviews, December 2016
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1 tweeter
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1 Facebook page

Citations

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1 Dimensions

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22 Mendeley
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Title
Prognostic biomarkers to identify patients destined to develop severe Crohn’s disease who may benefit from early biological therapy: protocol for a systematic review, meta-analysis and external validation
Published in
Systematic Reviews, December 2016
DOI 10.1186/s13643-016-0383-5
Pubmed ID
Authors

Halligan, S., Halligan, S., Boone, D., Bhatnagar, G., Ahmad, Tariq, Bloom, S., Rodriguez-Justo, M., Taylor, S. A., Mallett, S.

Abstract

It is believed increasingly that patients with severe Crohn's disease are best treated early with biological therapy, which may ameliorate subsequent disease course and diminish long-term complications. However, we cannot predict currently which new presentations of Crohn's disease are destined to develop severe disease so treatment cannot be targeted to the most appropriate patients. Accordingly, via systematic review and meta-analysis we aim to identify if biomarkers of disease activity are able to predict development of severe disease. We will search the primary literature and conference proceedings for studies of biomarkers of all types including clinical, endoscopic, radiological, faecal, urinary, serological, genetic, and histological. Precise definition of "severe" disease is elusive so we will include sensitivity analysis to account for different definitions. We will use the CHARMS checklist to frame our question and to extract data. We will extract the study design, setting, participant characteristics, biomarker(s) investigated, and study outcomes. Bias will be assessed via the PROBAST tool. We will present the results using narrative and graphical methods. We will present the summary by meta-analysis where there are sufficient studies with reasonable homogeneity, using methods appropriate to the type of data extracted. Heterogeneity will be presented via Forest and ROC plots. If this systematic review and meta-analysis identifies biomarkers that appear sufficiently predictive for subsequent severe disease course, we aim to combine them in a predictive model, followed by external validation using individual patient data. A predictive model able to identify new presentations of Crohn's disease destined to develop severe disease subsequently would have considerable clinical utility for patient management. PROSPERO CRD42016029363 .

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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 23%
Researcher 3 14%
Student > Ph. D. Student 3 14%
Student > Bachelor 2 9%
Professor 2 9%
Other 5 23%
Unknown 2 9%
Readers by discipline Count As %
Medicine and Dentistry 4 18%
Pharmacology, Toxicology and Pharmaceutical Science 3 14%
Agricultural and Biological Sciences 2 9%
Nursing and Health Professions 2 9%
Biochemistry, Genetics and Molecular Biology 2 9%
Other 2 9%
Unknown 7 32%

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 05 December 2016.
All research outputs
#6,334,299
of 8,729,235 outputs
Outputs from Systematic Reviews
#582
of 720 outputs
Outputs of similar age
#192,848
of 298,628 outputs
Outputs of similar age from Systematic Reviews
#34
of 38 outputs
Altmetric has tracked 8,729,235 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 720 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.4. This one is in the 15th percentile – i.e., 15% 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 298,628 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.