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使用真实世界数据评估玻璃体内抗血管内皮生长因子药物的安全性:观察性研究中的方法学挑战。

Assessing intravitreal anti-VEGF drug safety using real-world data: methodological challenges in observational research.

机构信息

Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy.

Research Centre on Public Health (CESP), University of Milan-Bicocca, Milan, Italy.

出版信息

Expert Opin Drug Saf. 2022 Feb;21(2):205-214. doi: 10.1080/14740338.2021.1957829. Epub 2021 Jul 27.

Abstract

INTRODUCTION

It is generally acknowledged that the ocular safety profile of intravitreal anti-VEGF drugs is acceptable, while the burden of systemic safety of these intravitreal agents is still being debated. The evaluation of the systemic safety of these drugs using real-world data (RWD), such as spontaneous reporting systems (SRS), electronic medical records (EMRs) and claims databases has several advantages, including the capture of outcomes among real-world populations over long observation periods. Nevertheless, there is a relatively small body of research exploring the post-marketing safety of these drugs.

AREAS COVERED

The aim of this scoping review is to outline and discuss some of the methodological challenges to be faced when investigating the systemic safety of intravitreal anti-VEGF drugs using different sources of RWD.

EXPERT OPINION

Such challenges include the selection of the most suitable data source, taking into account how well drug utilization is captured and whether the outcomes and covariates of interest can be captured. The strengths and limitations of some analytic methods that can be used to quantify risk, such as the intention-to-treat approach and the as-treated approach, complement each other, and using these together provides a more balanced analysis.

摘要

简介

人们普遍认为,玻璃体内抗血管内皮生长因子(VEGF)药物的眼部安全性是可以接受的,而这些玻璃体内药物的全身安全性负担仍存在争议。使用真实世界数据(RWD),如自发报告系统(SRS)、电子病历(EMR)和理赔数据库,评估这些药物的全身安全性具有几个优势,包括在长时间观察期间捕捉现实人群中的结果。然而,探索这些药物上市后安全性的研究相对较少。

涵盖领域

本综述的目的是概述和讨论在使用不同来源的 RWD 研究玻璃体内抗 VEGF 药物的全身安全性时所面临的一些方法学挑战。

专家意见

这些挑战包括选择最合适的数据来源,考虑药物利用的情况以及是否可以捕获感兴趣的结局和协变量。一些可用于量化风险的分析方法(如意向治疗法和实际治疗法)各有优缺点,相互补充,共同使用可以提供更平衡的分析。

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