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Use of real-world evidence in meta-analyses and cost-effectiveness models

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Date
2020-06
Dewey
Economie sociale
Sujet
Anticoagulants; atrial fibrillation; meta-analysis; cost-effectiveness; real-world evidences; troke prevention
JEL code
I.I2.I20; I.I1.I19
Journal issue
Journal of Medical Economics
Volume
23
Number
10
Publication date
06-2020
Article pages
1053-1060
Publisher
Taylor & Francis
DOI
http://dx.doi.org/10.1080/13696998.2020.1792917
URI
https://basepub.dauphine.fr/handle/123456789/21535
Collections
  • LEDa : Publications
Metadata
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Author
Bowrin, Kevin
167303 Bayer Corporation
Briere, Jean-Baptiste
73660 BAYER AG
Lévy, Pierre
163517 Laboratoire d'Economie et de Gestion des Organisations de Santé [Legos]
559342 Laboratoire d'Economie de Dauphine [LEDa]
Toumi, Mondher
527022 Centre d'études et de recherche sur les services de santé et la qualité de vie [CEReSS]
Millier, Aurélie
147877 Creativ-Ceutical France
Type
Article accepté pour publication ou publié
Abstract (EN)
Real-world evidence (RWE) provides external validity, supplementing and enhancing the randomized controlled trial data with valuable information on patient behaviors and outcomes, turning efficacy and safety results into real-world effectiveness and risks, but the use of RWE is associated with challenges. The objectives of this communication were to (1) summarize all guidance on how to conduct an RWE meta-analysis (MA) and how to develop an RWE cost-effectiveness model, (2) to describe our experience, challenges faced and solutions identified, (3) to provide recommendations on how to conduct such analyses. No formal guidelines on how to conduct an RWE MA or to develop an RWE cost-effectiveness model were identified. Using the context of non-vitamin K antagonist oral anticoagulants in stroke prevention in atrial fibrillation, we conducted an RWE MA, after having identified sources of uncertainty. We then implemented the results in an RWE cost-effectiveness model, defined as a model where all inputs come from RWE, including all parameters related to treatment effect. Based on challenges faced, our first recommendation relates to the necessity of conducting sensitivity analyses, either based on clinical or methodological considerations. Our second recommendation is the need for extensive collaboration with a wide range of experts, during the development of the analyses protocols, the implementation of the analyses and the interpretation of the results. RWE may address a number of gaps related to the treatment effect, and RWE economic evaluations for the treatment effect can provide extremely valuable insights into real-world economic value of interventions. As the increased recognition of the value of RWE could influence health technology assessment decision, and current practices, this communication supports the urgent need of more formal guidelines.

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