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Invited Commentary: Go BIG and Go Global-Executing Large-Scale, Multisite Pharmacoepidemiologic Studies Using Real-World Data

Maro, Judith C ; Toh, Sengwee

American journal of epidemiology, 2022-07, Vol.191 (8), p.1368-1371 [Periódico revisado por pares]

United States: Oxford Publishing Limited (England)

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  • Título:
    Invited Commentary: Go BIG and Go Global-Executing Large-Scale, Multisite Pharmacoepidemiologic Studies Using Real-World Data
  • Autor: Maro, Judith C ; Toh, Sengwee
  • Assuntos: Clinical trials ; Computer architecture ; Data models ; Databases, Factual ; Epidemiology ; Humans ; International boundaries ; Invited ; Medical equipment ; Patients ; Pharmacoepidemiology ; Pharmacology ; Population studies
  • É parte de: American journal of epidemiology, 2022-07, Vol.191 (8), p.1368-1371
  • Notas: ObjectType-Article-1
    SourceType-Scholarly Journals-1
    ObjectType-Feature-2
    ObjectType-Commentary-3
    content type line 23
  • Descrição: At the time medical products are approved, we rarely know enough about their comparative safety and effectiveness vis-à-vis alternative therapies to advise patients and providers. Postmarket generation of evidence on rare adverse events following medical product exposure increasingly requires analysis of millions of longitudinal patient records that can provide complete capture of data on patient experiences. In the accompanying article by Pradhan et al. (Am J Epidemiology. 2022;191(8):1352-1367), the authors demonstrate how observational database studies are often the most practical approach, provided these databases are carefully chosen to be "fit for purpose." Distributed data networks with common data models have proliferated in the last 2 decades in pharmacoepidemiology, allowing efficient capture of patient data in a standardized and structured format across disparate real-world data sources. Use of common data models facilitates transparency by allowing standardized programming approaches that can be easily reproduced. The distributed data network architecture, combined with a common data approach, supports not only multisite observational studies but also pragmatic clinical trials. It also helps bridge international boundaries and further increases the sample size and diversity of study populations.
  • Editor: United States: Oxford Publishing Limited (England)
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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