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Adaptive trial designs: a review of barriers and opportunities

Overview of attention for article published in Trials, August 2012
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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 (95th percentile)

Mentioned by

blogs
4 blogs
twitter
6 tweeters

Citations

dimensions_citation
135 Dimensions

Readers on

mendeley
234 Mendeley
citeulike
1 CiteULike
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Title
Adaptive trial designs: a review of barriers and opportunities
Published in
Trials, August 2012
DOI 10.1186/1745-6215-13-145
Pubmed ID
Authors

John A Kairalla, Christopher S Coffey, Mitchell A Thomann, Keith E Muller

Abstract

Adaptive designs allow planned modifications based on data accumulating within a study. The promise of greater flexibility and efficiency stimulates increasing interest in adaptive designs from clinical, academic, and regulatory parties. When adaptive designs are used properly, efficiencies can include a smaller sample size, a more efficient treatment development process, and an increased chance of correctly answering the clinical question of interest. However, improper adaptations can lead to biased studies. A broad definition of adaptive designs allows for countless variations, which creates confusion as to the statistical validity and practical feasibility of many designs. Determining properties of a particular adaptive design requires careful consideration of the scientific context and statistical assumptions. We first review several adaptive designs that garner the most current interest. We focus on the design principles and research issues that lead to particular designs being appealing or unappealing in particular applications. We separately discuss exploratory and confirmatory stage designs in order to account for the differences in regulatory concerns. We include adaptive seamless designs, which combine stages in a unified approach. We also highlight a number of applied areas, such as comparative effectiveness research, that would benefit from the use of adaptive designs. Finally, we describe a number of current barriers and provide initial suggestions for overcoming them in order to promote wider use of appropriate adaptive designs. Given the breadth of the coverage all mathematical and most implementation details are omitted for the sake of brevity. However, the interested reader will find that we provide current references to focused reviews and original theoretical sources which lead to details of the current state of the art in theory and practice.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters 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 234 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 2%
United Kingdom 4 2%
Singapore 2 <1%
India 1 <1%
Sweden 1 <1%
Gambia 1 <1%
Norway 1 <1%
Unknown 219 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 63 27%
Student > Ph. D. Student 46 20%
Student > Master 22 9%
Other 17 7%
Professor 17 7%
Other 52 22%
Unknown 17 7%
Readers by discipline Count As %
Medicine and Dentistry 74 32%
Mathematics 28 12%
Psychology 22 9%
Agricultural and Biological Sciences 16 7%
Social Sciences 11 5%
Other 50 21%
Unknown 33 14%

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 23 October 2018.
All research outputs
#888,379
of 17,351,915 outputs
Outputs from Trials
#227
of 4,578 outputs
Outputs of similar age
#5,809
of 138,140 outputs
Outputs of similar age from Trials
#1
of 1 outputs
Altmetric has tracked 17,351,915 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,578 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has done particularly well, scoring higher than 95% 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 138,140 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them