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Guidance for a causal comparative effectiveness analysis emulating a target trial based on big real world evidence: when to start statin treatment.
Kuehne, Felicitas; Jahn, Beate; Conrads-Frank, Annette; Bundo, Marvin; Arvandi, Marjan; Endel, Florian; Popper, Niki; Endel, Gottfried; Urach, Christoph; Gyimesi, Michael; Murray, Eleanor J; Danaei, Goodarz; Gaziano, Thomas A; Pandya, Ankur; Siebert, Uwe.
Afiliação
  • Kuehne F; Department of Public Health, Health Services Research & Health Technology Assessment, Institute of Public Health, Medical Decision Making & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Hall iT, Austria.
  • Jahn B; Department of Public Health, Health Services Research & Health Technology Assessment, Institute of Public Health, Medical Decision Making & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Hall iT, Austria.
  • Conrads-Frank A; Department of Public Health, Health Services Research & Health Technology Assessment, Institute of Public Health, Medical Decision Making & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Hall iT, Austria.
  • Bundo M; Department of Public Health, Health Services Research & Health Technology Assessment, Institute of Public Health, Medical Decision Making & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Hall iT, Austria.
  • Arvandi M; Department of Public Health, Health Services Research & Health Technology Assessment, Institute of Public Health, Medical Decision Making & Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics & Technology, Hall iT, Austria.
  • Endel F; DEXHELPP, Vienna, Austria.
  • Popper N; DEXHELPP, Vienna, Austria.
  • Endel G; TU Wien, Research Unit of Information and Software Engineering, Austria.
  • Urach C; dwh GmbH, Simulation Services & Technical Solutions, Austria.
  • Gyimesi M; Department EWG, Main Association of Austrian Social Security Institutions, Vienna, Austria.
  • Murray EJ; dwh GmbH, Simulation Services & Technical Solutions, Austria.
  • Danaei G; Austrian Public Health Institute, Austria.
  • Gaziano TA; Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA.
  • Pandya A; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA.
  • Siebert U; Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA 02115, USA.
J Comp Eff Res ; 8(12): 1013-1025, 2019 09.
Article em En | MEDLINE | ID: mdl-31512926
Aim: The aim of this project is to describe a causal (counterfactual) approach for analyzing when to start statin treatment to prevent cardiovascular disease using real-world evidence. Methods: We use directed acyclic graphs to operationalize and visualize the causal research question considering selection bias, potential time-independent and time-dependent confounding. We provide a study protocol following the 'target trial' approach and describe the data structure needed for the causal assessment. Conclusion: The study protocol can be applied to real-world data, in general. However, the structure and quality of the database play an essential role for the validity of the results, and database-specific potential for bias needs to be explicitly considered.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Cardiovasculares / Inibidores de Hidroximetilglutaril-CoA Redutases / Pesquisa Comparativa da Efetividade Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Comp Eff Res Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Doenças Cardiovasculares / Inibidores de Hidroximetilglutaril-CoA Redutases / Pesquisa Comparativa da Efetividade Tipo de estudo: Guideline / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: J Comp Eff Res Ano de publicação: 2019 Tipo de documento: Article