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孕期药物安全性研究中的公平比较:混杂因素控制的先进方法概述

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

作者信息

Wood Mollie E, Lapane Kate L, van Gelder Marleen M H J, Rai Dheeraj, Nordeng Hedvig M E

机构信息

PharmacoEpidemiology and Drug Safety Research Group, School of Pharmacy, University of Oslo, Norway.

Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA.

出版信息

Pharmacoepidemiol Drug Saf. 2018 Feb;27(2):140-147. doi: 10.1002/pds.4336. Epub 2017 Oct 17.

Abstract

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.

摘要

了解孕期用药的安全性依赖于观察性研究

然而,观察性研究中的混杂因素对从观察性数据得出的估计值的有效性构成了威胁。诸如边际结构模型和倾向校准等更新的方法已经出现,以处理复杂的混杂问题,但这些方法在孕期用药文献中的应用有限。在本文中,我们概述了用于控制混杂因素的更新的先进方法,并展示了这些方法如何与孕期用药安全性研究相关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/12f9/6646901/ea047fcf0f57/PDS-27-140-g001.jpg

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