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A multi-arm multi-stage clinical trial design for binary outcomes with application to tuberculosis

Overview of attention for article published in BMC Medical Research Methodology, November 2013
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  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Average Attention Score compared to outputs of the same age and source

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55 Mendeley
Title
A multi-arm multi-stage clinical trial design for binary outcomes with application to tuberculosis
Published in
BMC Medical Research Methodology, November 2013
DOI 10.1186/1471-2288-13-139
Pubmed ID
Authors

Daniel J Bratton, Patrick PJ Phillips, Mahesh KB Parmar

Abstract

Randomised controlled trials are becoming increasingly costly and time-consuming. In 2011, Royston and colleagues proposed a particular class of multi-arm multi-stage (MAMS) designs intended to speed up the evaluation of new treatments in phase II and III clinical trials. Their design, which controls the type I error rate and power for each pairwise comparison, discontinues randomisation to poorly performing arms at interim analyses if they fail to show a pre-specified level of benefit over the control arm. Arms in which randomisation is continued to the final stage of the trial are compared against the control on a definitive time-to-event outcome measure. To increase efficiency, interim comparisons can be made on an intermediate time-to-event outcome which is on the causal pathway to the definitive outcome.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 24%
Student > Master 6 11%
Student > Ph. D. Student 4 7%
Professor 3 5%
Other 3 5%
Other 8 15%
Unknown 18 33%
Readers by discipline Count As %
Medicine and Dentistry 12 22%
Mathematics 6 11%
Agricultural and Biological Sciences 3 5%
Biochemistry, Genetics and Molecular Biology 2 4%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Other 10 18%
Unknown 20 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 29 July 2020.
All research outputs
#7,124,984
of 22,731,677 outputs
Outputs from BMC Medical Research Methodology
#1,051
of 2,004 outputs
Outputs of similar age
#66,678
of 212,302 outputs
Outputs of similar age from BMC Medical Research Methodology
#11
of 24 outputs
Altmetric has tracked 22,731,677 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 2,004 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. This one is in the 46th percentile – i.e., 46% 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 212,302 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 50% of its contemporaries.