↓ Skip to main content

Lessons learned from IDeAl — 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials

Overview of attention for article published in Orphanet Journal of Rare Diseases, May 2018
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
33 Mendeley
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
Lessons learned from IDeAl — 33 recommendations from the IDeAl-net about design and analysis of small population clinical trials
Published in
Orphanet Journal of Rare Diseases, May 2018
DOI 10.1186/s13023-018-0820-8
Pubmed ID
Authors

Ralf-Dieter Hilgers, Malgorzata Bogdan, Carl-Fredrik Burman, Holger Dette, Mats Karlsson, Franz König, Christoph Male, France Mentré, Geert Molenberghs, Stephen Senn

Abstract

IDeAl (Integrated designs and analysis of small population clinical trials) is an EU funded project developing new statistical design and analysis methodologies for clinical trials in small population groups. Here we provide an overview of IDeAl findings and give recommendations to applied researchers. The description of the findings is broken down by the nine scientific IDeAl work packages and summarizes results from the project's more than 60 publications to date in peer reviewed journals. In addition, we applied text mining to evaluate the publications and the IDeAl work packages' output in relation to the design and analysis terms derived from in the IRDiRC task force report on small population clinical trials. The results are summarized, describing the developments from an applied viewpoint. The main result presented here are 33 practical recommendations drawn from the work, giving researchers a comprehensive guidance to the improved methodology. In particular, the findings will help design and analyse efficient clinical trials in rare diseases with limited number of patients available. We developed a network representation relating the hot topics developed by the IRDiRC task force on small population clinical trials to IDeAl's work as well as relating important methodologies by IDeAl's definition necessary to consider in design and analysis of small-population clinical trials. These network representation establish a new perspective on design and analysis of small-population clinical trials. IDeAl has provided a huge number of options to refine the statistical methodology for small-population clinical trials from various perspectives. A total of 33 recommendations developed and related to the work packages help the researcher to design small population clinical trial. The route to improvements is displayed in IDeAl-network representing important statistical methodological skills necessary to design and analysis of small-population clinical trials. The methods are ready for use.

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Other 4 12%
Student > Ph. D. Student 4 12%
Researcher 4 12%
Student > Master 4 12%
Student > Bachelor 2 6%
Other 6 18%
Unknown 9 27%
Readers by discipline Count As %
Medicine and Dentistry 6 18%
Agricultural and Biological Sciences 4 12%
Mathematics 3 9%
Biochemistry, Genetics and Molecular Biology 2 6%
Nursing and Health Professions 2 6%
Other 6 18%
Unknown 10 30%
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 21 March 2022.
All research outputs
#6,615,081
of 23,390,392 outputs
Outputs from Orphanet Journal of Rare Diseases
#923
of 2,689 outputs
Outputs of similar age
#113,919
of 326,515 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#21
of 47 outputs
Altmetric has tracked 23,390,392 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 2,689 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has gotten more attention than average, scoring higher than 63% 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 326,515 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 64% of its contemporaries.
We're also able to compare this research output to 47 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 55% of its contemporaries.