↓ Skip to main content

Directions for new developments on statistical design and analysis of small population group trials

Overview of attention for article published in Orphanet Journal of Rare Diseases, June 2016
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
7 X users
facebook
2 Facebook pages

Citations

dimensions_citation
33 Dimensions

Readers on

mendeley
56 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
Directions for new developments on statistical design and analysis of small population group trials
Published in
Orphanet Journal of Rare Diseases, June 2016
DOI 10.1186/s13023-016-0464-5
Pubmed ID
Authors

Ralf-Dieter Hilgers, Kit Roes, Nigel Stallard, for the IDeAl, Asterix and InSPiRe project groups

Abstract

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Netherlands 1 2%
Unknown 54 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 21%
Student > Ph. D. Student 10 18%
Student > Master 8 14%
Professor > Associate Professor 7 13%
Other 6 11%
Other 10 18%
Unknown 3 5%
Readers by discipline Count As %
Medicine and Dentistry 15 27%
Nursing and Health Professions 6 11%
Mathematics 6 11%
Pharmacology, Toxicology and Pharmaceutical Science 5 9%
Agricultural and Biological Sciences 3 5%
Other 10 18%
Unknown 11 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 09 February 2017.
All research outputs
#5,452,627
of 25,394,764 outputs
Outputs from Orphanet Journal of Rare Diseases
#771
of 3,110 outputs
Outputs of similar age
#90,409
of 368,511 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#12
of 51 outputs
Altmetric has tracked 25,394,764 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,110 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has gotten more attention than average, scoring higher than 74% 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 368,511 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 73% of its contemporaries.
We're also able to compare this research output to 51 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.