Evolving cohesion metrics of a research network on rare diseases: a longitudinal study over 14 years

Amat, Carlos Benito; Perruchas, François

doi:10.1007/s11192-016-1952-z

Cited by 5 publications

(2 citation statements)

References 33 publications

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“…Publications amount also depends on the disease distribution: it has also been shown that for diseases with a high concentration in prevalence, such as Behçet’s disease, the countries where it is the most prevalent might not be the biggest publication sources [ 5 ]. Another institutional factor of importance is the development of referring centres, structures of high expertise on rare diseases both clinically and scientifically, and their ability to form collaboration on a national level [ 7 , 17 , 18 ]. These efforts can be loosely correlated with actual disease prevalence.…”

Section: Discussionmentioning

confidence: 99%

Assessing rare diseases prevalence using literature quantification

Shourick

Maxime

Anne-Sophie

2021

Orphanet J Rare Dis

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Introduction Estimating the prevalence of diseases is crucial for the organization of healthcare. The amount of literature on a rare pathology could help differentiate between rare and very rare diseases. The objective of this work was to evaluate to what extent the number of publications can be used to predict the prevalence of a given pathology. Methods We queried Orphanet for the global prevalence class for all conditions for which it was available. For these pathologies, we cross-referenced the Orphanet, MeSH, and OMIM vocabularies to assess the number of publication available on Pubmed using three different query strategies (one proposed in the literature, and two built specifically for this study). We first studied the association of the number of publications obtained by each of these query strategies with the prevalence class, then their predictive ability. Results Class prevalence was available for 3128 conditions, 2970 had a prevalence class < 1/1,000,000, 41 of 1–9/1,000,000, 84 of 1–9/100,000, and 33 of 1–9/10,000. We show a significant association and excellent predictive performance of the number of publication, with an AUC over 94% for the best query strategy. Conclusion Our study highlights the link and the excellent predictive performance of the number of publications on the prevalence of rare diseases provided by Orphanet.

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Section: Discussionmentioning

confidence: 99%

Assessing rare diseases prevalence using literature quantification

Shourick

Maxime

Anne-Sophie

2021

Orphanet J Rare Dis

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“…Each rare disease research project is fragmentary and dispersed in each country because of the small number of patients (Ayme and Schmidtke 2007). Substantial research on individual rare diseases has been made and collaboration of a research network on rare diseases analyzed by social network analysis was reported (Amat and Perruchas 2016), but there are few reports comprehensively analyzing trends concerning how research and development have been performed for rare diseases generally.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of correlations of research and development indicators for rare diseases among Japan, the US, and Europe

Mizoguchi

Kano

2019

Scientometrics

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There are many rare diseases and biomedical research efforts for treatment of each disease have been ongoing. However, few reports are available to analyze overall trends for how research and development have been performed for rare diseases generally. In this research, the correlations between research and development indicators of rare diseases were examined with international comparisons among Japan, the US, and Europe. The correlation between the number of clinical studies and orphan drug designations was lower in Japan than that in the US and Europe, while the correlation between the number of orphan drug designations and orphan drug approvals was higher in Japan than in the US and Europe. This analysis clarified differences in the orphan drug designation system, operational characteristics, and beneficial points in the regions. Based on the findings of the analysis of the research/regulatory system, earlier time of orphan drug designation in Japan was proposed as a policy implication.

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Symbolic capital and the basket of 8: What changed after the creation of the basket?

Chipidza

Tripp

2021

Decision Support Systems

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Evolving cohesion metrics of a research network on rare diseases: a longitudinal study over 14 years

Cited by 5 publications

References 33 publications

Assessing rare diseases prevalence using literature quantification

Assessing rare diseases prevalence using literature quantification

Comparative analysis of correlations of research and development indicators for rare diseases among Japan, the US, and Europe

Symbolic capital and the basket of 8: What changed after the creation of the basket?

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