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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 14% |
| United States | 1 | 14% |
| Canada | 1 | 14% |
| Italy | 1 | 14% |
| Australia | 1 | 14% |
| Spain | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 71% |
| Scientists | 1 | 14% |
| Practitioners (doctors, other healthcare professionals) | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 603 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 1% |
| United Kingdom | 8 | 1% |
| Germany | 5 | <1% |
| Brazil | 4 | <1% |
| Canada | 4 | <1% |
| Switzerland | 1 | <1% |
| Norway | 1 | <1% |
| Korea, Republic of | 1 | <1% |
| Netherlands | 1 | <1% |
| Other | 8 | 1% |
| Unknown | 561 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 138 | 23% |
| Student > Ph. D. Student | 98 | 16% |
| Student > Master | 67 | 11% |
| Other | 59 | 10% |
| Professor | 44 | 7% |
| Other | 127 | 21% |
| Unknown | 70 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 182 | 30% |
| Mathematics | 76 | 13% |
| Agricultural and Biological Sciences | 64 | 11% |
| Psychology | 27 | 4% |
| Pharmacology, Toxicology and Pharmaceutical Science | 27 | 4% |
| Other | 123 | 20% |
| Unknown | 104 | 17% |
Attention Score in Context
This research output has an Altmetric Attention Score of 63. 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 08 June 2023.
All research outputs
#653,510
of 24,784,213 outputs
Outputs from Orphanet Journal of Rare Diseases
#55
of 2,971 outputs
Outputs of similar age
#1,133
of 83,988 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#1
of 9 outputs
Altmetric has tracked 24,784,213 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 2,971 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. 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 83,988 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 9 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