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Number Needed to Treat in Multiple Sclerosis Clinical Trials

Overview of attention for article published in Neurology and Therapy, February 2017
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Title
Number Needed to Treat in Multiple Sclerosis Clinical Trials
Published in
Neurology and Therapy, February 2017
DOI 10.1007/s40120-017-0063-y
Pubmed ID
Authors

Macaulay Okwuokenye, Annie Zhang, Amy Pace, Karl E. Peace

Abstract

Clinicians are expected to select a therapy based on their appraisal of evidence on benefit-to-risk profiles of therapies. In the management of relapsing-remitting multiple sclerosis (RRMS), evidence is typically expressed in terms of risk (proportion) of event, risk reduction, relative and hazard rate reduction, or relative reduction in the mean number of magnetic resonance imaging lesions. Interpreting treatment effect using these measures from a RRMS clinical trial is fairly reliable; however, this might not be the case when treatment effect is expressed in terms of the number needed to treat (NNT). The objective of this review is to discuss the utility of NNT in RRMS trials. This article presents an overview of the methodological definition and characteristics of NNT as well as the relative merit of NNT use in RRMS controlled clinical trials, where endpoints are typically time-to-event and frequency of recurrent events. The authors caution against using NNT in multiple sclerosis, a clinically heterogeneous disease that can change course and severity unpredictably. The authors also caution against the use of NNT to interpret results in comparative trials where the absolute risk difference is not statistically significant, computing NNT using the time-to-event endpoint at intermediate time points, computing NNT using the annualized relapse rate, and comparing NNT across trials.

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Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 17%
Student > Master 5 17%
Student > Ph. D. Student 3 10%
Student > Bachelor 2 7%
Student > Doctoral Student 2 7%
Other 7 23%
Unknown 6 20%
Readers by discipline Count As %
Medicine and Dentistry 15 50%
Neuroscience 3 10%
Agricultural and Biological Sciences 2 7%
Mathematics 1 3%
Physics and Astronomy 1 3%
Other 1 3%
Unknown 7 23%
Attention Score in Context

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 11 February 2017.
All research outputs
#18,531,724
of 22,953,506 outputs
Outputs from Neurology and Therapy
#336
of 420 outputs
Outputs of similar age
#310,266
of 420,233 outputs
Outputs of similar age from Neurology and Therapy
#6
of 6 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 420 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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