Literature DB >> 29688403

Stroke prevention in atrial fibrillation: re-defining 'real-world data' within the broader data universe.

Alexander C Fanaroff1, Jan Steffel2, John H Alexander1, Gregory Y H Lip3,4, Robert M Califf1,5, Renato D Lopes1.   

Abstract

Real-world data (RWD) has been defined as data generated outside of traditional randomized clinical trials (RCTs). Though RWD has received increasing attention from regulatory authorities and professional societies, dividing evidence into that derived from 'real-world' vs. 'non-real-world' sources provides only one element of a much larger framework for evidence evaluation. Evidence should be evaluated on the source of the data, the method of treatment allocation (whether any intervention being evaluated was assigned or simply observed as used in practice) and the context in which the evidence was generated (overall study design). Under this framework, RWD refers only to data source, and a study incorporates RWD when it primarily uses data collected for non-research purposes, such as insurance claims data or the electronic health record, regardless of study design. Separation of study design, data source, and context enables parallel evaluation of two critical elements: (i) whether a study can support claims of causal inference, which can be assured with a high degree of confidence only in studies where patients are assigned treatments by protocol; and (ii) whether the study population and clinical context mirror clinical practice, a strength of observational studies using data from clinical practice or administrative claims. In this review, we describe the strengths and weaknesses of observational and non-observational studies, and studies involving RWD and non-RWD, through the lens of anticoagulation for atrial fibrillation (AF). Observational studies employing RWD are useful for describing how oral anticoagulants are used in clinical practice, but generally cannot be used to make claims regarding comparative treatment effects. Questions regarding treatment effect generally are best answered through an RCT, and additional pragmatic RCTs are needed to compare different antithrombotic agents for the prevention of thrombotic events in AF.

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Year:  2018        PMID: 29688403     DOI: 10.1093/eurheartj/ehy236

Source DB:  PubMed          Journal:  Eur Heart J        ISSN: 0195-668X            Impact factor:   29.983


  5 in total

1.  When Can We Rely on Real-World Evidence to Evaluate New Medical Treatments?

Authors:  Gregory E Simon; Richard Platt; Jonathan H Watanabe; Andrew B Bindman; Alex John London; Michael Horberg; Adrian Hernandez; Robert M Califf
Journal:  Clin Pharmacol Ther       Date:  2021-05-19       Impact factor: 6.903

Review 2.  Randomized Trials Versus Common Sense and Clinical Observation: JACC Review Topic of the Week.

Authors:  Alexander C Fanaroff; Robert M Califf; Robert A Harrington; Christopher B Granger; John J V McMurray; Manesh R Patel; Deepak L Bhatt; Stephan Windecker; Adrian F Hernandez; C Michael Gibson; John H Alexander; Renato D Lopes
Journal:  J Am Coll Cardiol       Date:  2020-08-04       Impact factor: 24.094

3.  The use of UK primary care databases in health technology assessments carried out by the National Institute for health and care excellence (NICE).

Authors:  Thomas P Leahy; Sreeram Ramagopalan; Cormac Sammon
Journal:  BMC Health Serv Res       Date:  2020-07-22       Impact factor: 2.655

4.  What if there is no prospective, double blind, randomised trial?

Authors:  J R de Groot
Journal:  Neth Heart J       Date:  2019-10       Impact factor: 2.380

5.  Creation and Implementation of a Prospective and Multicentric Database of Patients with Acute Myocardial Infarction: RIAM.

Authors:  Jacqueline Vaz; Anibal Pereira Abelin; Marcia Moura Schmidt; Pedro Piccaro de Oliveira; Carlos A M Gottschall; Clarissa Garcia Rodrigues; Alexandre Schaan de Quadros
Journal:  Arq Bras Cardiol       Date:  2020 May-Jun       Impact factor: 2.000

  5 in total

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