Increase transparency and reproducibility of real‐world evidence in rare diseases through disease‐specific Federated Data Networks

Author:

van Baalen Valerie1ORCID,Didden Eva‐Maria1,Rosenberg Daniel1,Bardenheuer Kristina2,van Speybroeck Michel3,Brand Monika1

Affiliation:

1. Global Epidemiology Office of the Chief Medical Officer Johnson & Johnson Basel Switzerland

2. Health Economics, Market Access and Reimbursement EMEA Real‐World Evidence and Value‐based Health Care Johnson & Johnson Neuss Germany

3. Data Science IT EMEA Johnson & Johnson Technology Beerse Belgium

Abstract

AbstractPurposeIn rare diseases, real‐world evidence (RWE) generation is often restricted due to small patient numbers and global geographic distribution. A federated data network (FDN) approach brings together multiple data sources harmonized for collaboration to increase the power of observational research. In this paper, we review how to increase reproducibility and transparency of RWE studies in rare diseases through disease‐specific FDNs.MethodTo be successful, a multiple stakeholder scientific FDN collaboration requires a strong governance model in place. In such a model, each database owner remains in full control regarding the use of and access to patient‐level data and is responsible for data privacy, ethical, and legal compliance. Provided that all this is well documented and good database descriptions are in place, such a governance model results in increased transparency, while reproducibility is achieved through data curation and harmonization, and distributed analytical methods.ResultsLeveraging the OHDSI community set of methods and tools, two rare disease‐specific FDNs are discussed in more detail. For multiple myeloma, HONEUR—the Haematology Outcomes Network in Europe—has built a strong community among the data partners dedicated to scientific exchange and research. To advance scientific knowledge in pulmonary hypertension (PH) an FDN, called PHederation, was established to form a partnership of research institutions with PH databases coming from diverse origins.

Funder

Johnson and Johnson

Publisher

Wiley

Reference36 articles.

1. About Rare Diseases.Orphanet.2012https://www.orpha.net/consor/cgi-bin/Education_AboutRareDiseases.php?lng=EN

2. FDA.Rare Diseases: Natural History Studies for Drug Development.2019.

3. ENCePP.The European network of centres for pharmacoepidemiology and pharmacovigilance. Guide on Methodological Standards in Pharmacoepidemiology (Revision 11).EMA/95098/2010; 2010.

4. Representation of rare diseases in health information systems: The orphanet approach to serve a wide range of end users

5. EUPAS4523.Disease characteristics and outcomes of pulmonary arterial hypertension in children and adolescents in real‐world clinical settings: systematic review of prospective observational registries.https://catalogues.ema.europa.eu/node/1697/administrative-details

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3