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Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control

Understanding the safety of medication use during pregnancy relies on observational studies: However, confounding in observational studies poses a threat to the validity of estimates obtained from observational data. Newer methods, such as marginal structural models and propensity calibration, have...

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Detalles Bibliográficos
Autores principales: Wood, Mollie E., Lapane, Kate L., van Gelder, Marleen M.H.J., Rai, Dheeraj, Nordeng, Hedvig M.E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646901/
https://www.ncbi.nlm.nih.gov/pubmed/29044735
http://dx.doi.org/10.1002/pds.4336
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author Wood, Mollie E.
Lapane, Kate L.
van Gelder, Marleen M.H.J.
Rai, Dheeraj
Nordeng, Hedvig M.E.
author_facet Wood, Mollie E.
Lapane, Kate L.
van Gelder, Marleen M.H.J.
Rai, Dheeraj
Nordeng, Hedvig M.E.
author_sort Wood, Mollie E.
collection PubMed
description Understanding the safety of medication use during pregnancy relies on observational studies: However, confounding in observational studies poses a threat to the validity of estimates obtained from observational data. Newer methods, such as marginal structural models and propensity calibration, have emerged to deal with complex confounding problems, but these methods have seen limited uptake in the pregnancy medication literature. In this article, we provide an overview of newer advanced methods for confounding control and show how these methods are relevant for pregnancy medication safety studies.
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spelling pubmed-66469012019-07-31 Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control Wood, Mollie E. Lapane, Kate L. van Gelder, Marleen M.H.J. Rai, Dheeraj Nordeng, Hedvig M.E. Pharmacoepidemiol Drug Saf Reviews Understanding the safety of medication use during pregnancy relies on observational studies: However, confounding in observational studies poses a threat to the validity of estimates obtained from observational data. Newer methods, such as marginal structural models and propensity calibration, have emerged to deal with complex confounding problems, but these methods have seen limited uptake in the pregnancy medication literature. In this article, we provide an overview of newer advanced methods for confounding control and show how these methods are relevant for pregnancy medication safety studies. John Wiley and Sons Inc. 2017-10-17 2018-02 /pmc/articles/PMC6646901/ /pubmed/29044735 http://dx.doi.org/10.1002/pds.4336 Text en © 2017 The Authors. Pharmacoepidemiology & Drug Safety Published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Wood, Mollie E.
Lapane, Kate L.
van Gelder, Marleen M.H.J.
Rai, Dheeraj
Nordeng, Hedvig M.E.
Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control
title Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control
title_full Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control
title_fullStr Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control
title_full_unstemmed Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control
title_short Making fair comparisons in pregnancy medication safety studies: An overview of advanced methods for confounding control
title_sort making fair comparisons in pregnancy medication safety studies: an overview of advanced methods for confounding control
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6646901/
https://www.ncbi.nlm.nih.gov/pubmed/29044735
http://dx.doi.org/10.1002/pds.4336
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