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An overview of the impact of rare disease characteristics on research methodology

Overview of attention for article published in Orphanet Journal of Rare Diseases, January 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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3 news outlets
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7 X users

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64 Dimensions

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130 Mendeley
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Title
An overview of the impact of rare disease characteristics on research methodology
Published in
Orphanet Journal of Rare Diseases, January 2018
DOI 10.1186/s13023-017-0755-5
Pubmed ID
Authors

Danielle Whicher, Sarah Philbin, Naomi Aronson

Abstract

About 30 million individuals in the United States are living with a rare disease, which by definition have a prevalence of 200,000 or fewer cases in the United States ([National Organization for Rare Disorders], [About NORD], [2016]). Disease heterogeneity and geographic dispersion add to the difficulty of completing robust studies in small populations. Improving the ability to conduct research on rare diseases would have a significant impact on population health. The purpose of this paper is to raise awareness of methodological approaches that can address the challenges to conducting robust research on rare diseases. We conducted a landscape review of available methodological and analytic approaches to address the challenges of rare disease research. Our objectives were to: 1. identify algorithms for matching study design to rare disease attributes and the methodological approaches applicable to these algorithms; 2. draw inferences on how research communities and infrastructure can contribute to the efficiency of research on rare diseases; and 3. to describe methodological approaches in the rare disease portfolio of the Patient-Centered Outcomes Research Institute (PCORI), a funder promoting both rare disease research and research infrastructure. We identified three algorithms for matching study design to rare disease or intervention characteristics (Gagne, et.al, BMJ 349:g6802, 2014); (Gupta, et.al, J Clin Epidemiol 64:1085-1094, 2011); (Cornu, et. al, Orphet J Rare Dis 8:48,2012) and summarized the applicable methodological and analytic approaches. From this literature we were also able to draw inferences on how an effective research infrastructure can set an agenda, prioritize studies, accelerate accrual, catalyze patient engagement and terminate poorly performing studies. Of the 24 rare disease projects in the PCORI portfolio, 11 are randomized controlled trials (RCTs) using standard designs. Thirteen are observational studies using case-control, prospective cohort, or natural history designs. PCORI has supported the development of 9 Patient-Powered Research Networks (PPRNs) focused on rare diseases. Matching research design to attributes of rare diseases and interventions can facilitate the completion of RCTs that are adequately powered. An effective research infrastructure can improve efficiency and avoid waste in rare disease research. Our review of the PCORI research portfolio demonstrates that it is feasible to conduct RCTs in rare disease. However, most of these studies are using standard RCT designs. This suggests that use of a broader array of methodological approaches to RCTs --such as adaptive trials, cross-over trials, and early escape designs can improve the productivity of robust research in rare diseases.

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

Geographical breakdown

Country Count As %
Unknown 130 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 21 16%
Researcher 17 13%
Student > Ph. D. Student 14 11%
Student > Doctoral Student 10 8%
Student > Bachelor 9 7%
Other 25 19%
Unknown 34 26%
Readers by discipline Count As %
Medicine and Dentistry 32 25%
Biochemistry, Genetics and Molecular Biology 17 13%
Nursing and Health Professions 11 8%
Pharmacology, Toxicology and Pharmaceutical Science 8 6%
Agricultural and Biological Sciences 5 4%
Other 20 15%
Unknown 37 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 30. 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 30 September 2022.
All research outputs
#1,156,304
of 23,443,716 outputs
Outputs from Orphanet Journal of Rare Diseases
#111
of 2,697 outputs
Outputs of similar age
#29,419
of 443,494 outputs
Outputs of similar age from Orphanet Journal of Rare Diseases
#4
of 36 outputs
Altmetric has tracked 23,443,716 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,697 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 443,494 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 93% of its contemporaries.
We're also able to compare this research output to 36 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.