↓ Skip to main content

Adaptive design methods in clinical trials – a review

Overview of attention for article published in Orphanet Journal of Rare Diseases, May 2008
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#24 of 1,620)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

news
1 news outlet
blogs
7 blogs
twitter
9 tweeters
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
294 Dimensions

Readers on

mendeley
528 Mendeley
citeulike
4 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Adaptive design methods in clinical trials – a review
Published in
Orphanet Journal of Rare Diseases, May 2008
DOI 10.1186/1750-1172-3-11
Pubmed ID
Authors

Shein-Chung Chow, Mark Chang

Abstract

In recent years, the use of adaptive design methods in clinical research and development based on accrued data has become very popular due to its flexibility and efficiency. Based on adaptations applied, adaptive designs can be classified into three categories: prospective, concurrent (ad hoc), and retrospective adaptive designs. An adaptive design allows modifications made to trial and/or statistical procedures of ongoing clinical trials. However, it is a concern that the actual patient population after the adaptations could deviate from the originally target patient population and consequently the overall type I error (to erroneously claim efficacy for an infective drug) rate may not be controlled. In addition, major adaptations of trial and/or statistical procedures of on-going trials may result in a totally different trial that is unable to address the scientific/medical questions the trial intends to answer. In this article, several commonly considered adaptive designs in clinical trials are reviewed. Impacts of ad hoc adaptations (protocol amendments), challenges in by design (prospective) adaptations, and obstacles of retrospective adaptations are described. Strategies for the use of adaptive design in clinical development of rare diseases are discussed. Some examples concerning the development of Velcade intended for multiple myeloma and non-Hodgkin's lymphoma are given. Practical issues that are commonly encountered when implementing adaptive design methods in clinical trials are also discussed.

Twitter Demographics

The data shown below were collected from the profiles of 9 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 528 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 11 2%
United Kingdom 8 2%
Germany 5 <1%
Canada 4 <1%
Brazil 4 <1%
Netherlands 2 <1%
Italy 1 <1%
Korea, Republic of 1 <1%
Norway 1 <1%
Other 8 2%
Unknown 483 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 132 25%
Student > Ph. D. Student 92 17%
Student > Master 59 11%
Other 54 10%
Professor 43 8%
Other 114 22%
Unknown 34 6%
Readers by discipline Count As %
Medicine and Dentistry 172 33%
Mathematics 75 14%
Agricultural and Biological Sciences 64 12%
Psychology 24 5%
Pharmacology, Toxicology and Pharmaceutical Science 21 4%
Other 108 20%
Unknown 64 12%

Attention Score in Context

This research output has an Altmetric Attention Score of 61. 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 May 2019.
All research outputs
#335,901
of 15,051,489 outputs
Outputs from Orphanet Journal of Rare Diseases
#24
of 1,620 outputs
Outputs of similar age
#1,972
of 125,842 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#1
of 15 outputs
Altmetric has tracked 15,051,489 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,620 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 98% 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 125,842 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 98% of its contemporaries.
We're also able to compare this research output to 15 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 93% of its contemporaries.