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Recommendations on clinical trial design for treatment of Mucopolysaccharidosis Type III

Overview of attention for article published in Orphanet Journal of Rare Diseases, June 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (81st percentile)

Mentioned by

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1 news outlet
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8 X users
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2 Facebook pages

Citations

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28 Dimensions

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67 Mendeley
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Title
Recommendations on clinical trial design for treatment of Mucopolysaccharidosis Type III
Published in
Orphanet Journal of Rare Diseases, June 2017
DOI 10.1186/s13023-017-0675-4
Pubmed ID
Authors

Arunabha Ghosh, Elsa Shapiro, Stewart Rust, Kathleen Delaney, Samantha Parker, Adam J Shaywitz, Adelaida Morte, Gillian Bubb, Maureen Cleary, Tien Bo, Christine Lavery, Brian W Bigger, Simon A Jones

Abstract

Mucopolysaccharidosis type III is a progressive, neurodegenerative lysosomal storage disorder for which there is currently no effective therapy. Though numerous potential therapies are in development, there are several challenges to conducting clinical research in this area. We seek to make recommendations on the approach to clinical research in MPS III, including the selection of outcome measures and trial endpoints, in order to improve the quality and impact of research in this area. An international workshop involving academic researchers, clinical experts and industry groups was held in June 2015, with presentations and discussions on disease pathophysiology, biomarkers, potential therapies and clinical outcome measures. A set of recommendations was subsequently prepared by a working group and reviewed by all delegates. We present a series of 11 recommendations regarding the conduct of clinical research, outcome measures and management of natural history data in Mucopolysaccharidosis type III. Improving the quality of clinical research in Mucopolysaccharidosis type III will require an open, collaborative and systematic approach between academic researchers, clinicians and industry. Natural history data should be published as soon as possible and ideally collated in a central repository. There should be agreement on outcome measures and instruments for evaluation of clinical outcomes to maximise the effectiveness of current and future clinical research.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 13%
Student > Ph. D. Student 8 12%
Other 8 12%
Researcher 8 12%
Student > Master 7 10%
Other 7 10%
Unknown 20 30%
Readers by discipline Count As %
Medicine and Dentistry 11 16%
Neuroscience 7 10%
Biochemistry, Genetics and Molecular Biology 6 9%
Nursing and Health Professions 4 6%
Unspecified 3 4%
Other 15 22%
Unknown 21 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 17 October 2018.
All research outputs
#2,336,447
of 24,384,616 outputs
Outputs from Orphanet Journal of Rare Diseases
#296
of 2,881 outputs
Outputs of similar age
#44,242
of 319,401 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#8
of 43 outputs
Altmetric has tracked 24,384,616 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 2,881 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 89% 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 319,401 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 86% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 81% of its contemporaries.