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Development of a Sensitive Outcome for Economical Drug Screening for Progressive Multiple Sclerosis Treatment

Overview of attention for article published in Frontiers in Neurology, August 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
2 X users

Citations

dimensions_citation
49 Dimensions

Readers on

mendeley
77 Mendeley
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Title
Development of a Sensitive Outcome for Economical Drug Screening for Progressive Multiple Sclerosis Treatment
Published in
Frontiers in Neurology, August 2016
DOI 10.3389/fneur.2016.00131
Pubmed ID
Authors

Peter Kosa, Danish Ghazali, Makoto Tanigawa, Chris Barbour, Irene Cortese, William Kelley, Blake Snyder, Joan Ohayon, Kaylan Fenton, Tanya Lehky, Tianxia Wu, Mark Greenwood, Govind Nair, Bibiana Bielekova

Abstract

Therapeutic advance in progressive multiple sclerosis (MS) has been very slow. Based on the transformative role magnetic resonance imaging (MRI) contrast-enhancing lesions had on drug development for relapsing-remitting MS, we consider the lack of sensitive outcomes to be the greatest barrier for developing new treatments for progressive MS. The purpose of this study was to compare 58 prospectively acquired candidate outcomes in the real-world situation of progressive MS trials to select and validate the best-performing outcome. The 1-year pre-treatment period of adaptively designed IPPoMS (ClinicalTrials.gov #NCT00950248) and RIVITaLISe (ClinicalTrials.gov #NCT01212094) Phase II trials served to determine the primary outcome for the subsequent blinded treatment phase by comparing 8 clinical, 1 electrophysiological, 1 optical coherence tomography, 7 MRI volumetric, 9 quantitative T1 MRI, and 32 diffusion tensor imaging MRI outcomes. Fifteen outcomes demonstrated significant progression over 1 year (Δ) in the predetermined analysis and seven out of these were validated in two independent cohorts. Validated MRI outcomes had limited correlations with clinical scales, relatively poor signal-to-noise ratios (SNR) and recorded overlapping values between healthy subjects and MS patients with moderate-severe disability. Clinical measures correlated better, even though each reflects a somewhat different disability domain. Therefore, using machine-learning techniques, we developed a combinatorial weight-adjusted disability score (CombiWISE) that integrates four clinical scales: expanded disability status scale (EDSS), Scripps neurological rating scale, 25 foot walk and 9 hole peg test. CombiWISE outperformed all clinical scales (Δ = 9.10%; p = 0.0003) and all MRI outcomes. CombiWISE recorded no overlapping values between healthy subjects and disabled MS patients, had high SNR, and predicted changes in EDSS in a longitudinal assessment of 98 progressive MS patients and in a cross-sectional cohort of 303 untreated subjects. One point change in EDSS corresponds on average to 7.50 point change in CombiWISE with a standard error of 0.10. The novel validated clinical outcome, CombiWISE, outperforms the current broadly utilized MRI brain atrophy outcome and more than doubles sensitivity in detecting clinical deterioration in progressive MS in comparison to the scale traditionally used for regulatory approval, EDSS.

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X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 19%
Student > Ph. D. Student 11 14%
Student > Master 8 10%
Professor 4 5%
Other 4 5%
Other 14 18%
Unknown 21 27%
Readers by discipline Count As %
Medicine and Dentistry 22 29%
Neuroscience 10 13%
Nursing and Health Professions 4 5%
Social Sciences 3 4%
Agricultural and Biological Sciences 2 3%
Other 10 13%
Unknown 26 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 06 October 2016.
All research outputs
#1,893,309
of 22,882,389 outputs
Outputs from Frontiers in Neurology
#886
of 11,802 outputs
Outputs of similar age
#36,120
of 344,201 outputs
Outputs of similar age from Frontiers in Neurology
#5
of 56 outputs
Altmetric has tracked 22,882,389 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,802 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done particularly well, scoring higher than 92% 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 344,201 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 89% of its contemporaries.
We're also able to compare this research output to 56 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.